WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Principal Machine Learning Software Engineer Job Description As a Machine Learning Engineer specializing in low-level performance optimization, you will play a critical role in helping our customers to advance AMD-based machine learning infrastructure and ensuring the efficient deployment of state-of-the-art large models. You will be part of a dynamic team working on groundbreaking projects and will be responsible for optimizing model execution, including GPU kernels, both for inference and training, in a multi-GPU and multi-node environment. Your contributions will directly impact our ability to deliver cutting-edge AI solutions efficiently and at scale. Key Responsibilities GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize the computational efficiency and reduce execution time while ensuring model accuracy. Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources. Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization. Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques. Model Quantization: Explore and apply model quantization techniques to reduce memory and computation overhead, especially for edge and cloud deployment. Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria. Collaboration: Collaborate closely with machine learning researchers, software engineers, and infrastructure teams to integrate optimized kernels and solutions into production systems. Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code. Qualifications A Bachelor, Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field or equivalent practical experience. Solid understanding of GPU accelerators like ONNX, DeepSpeed, VLLM Strong experience in low-level GPU kernel optimization. Proficiency in CUDA and GPU programming. Experience with distributed computing and multi-GPU environments. Proficiency in performance profiling and optimization tools. Solid programming skills in Python and/or C++. Experience with deep learning frameworks (e.g., JAX, PyTorch, TensorFlow). Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. Additional locations: Santa Clara, Austin, Remote LI-RL1 HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD's Employee Stock Purchase Plan. You'll also be eligible for competitive benefits described in more detail here. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

Summary:
Meta is in search of the world’s most creative and experienced engineering leaders. We embrace entrepreneurs as well as those who come from more established organizations. Machine Learning Engineering Managers are clearly characterized by progressive technical experience and demonstrated progression in management responsibility.
Required Skills:
Machine Learning Software Engineering Manager Responsibilities:
<ol>
<li>Be both highly technical and an effective people manager</li>
<li>Be a subject matter expert in an ML domain</li>
<li>Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area</li>
<li>Work with your team and cross functional partners to define and influence strategy</li>
<li>Drive roadmap creation and execution</li>
<li>Collaborate with various functions, drive engineering initiatives and have an impact at an organizational level</li>
<li>Participate in technical design</li>
<li>Measure the impact of your team and set clear expectations and goals</li>
<li>Work effectively with cross functional partners and stakeholders to set and achieve optimal outcomes</li>
</ol>
Minimum Qualifications:
<ol>
<li>8+ years of software engineering work experience, including hands-on technical management building large scale systems, algorithms, and toolsets within the Machine Learning domain</li>
<li>8+ years experience coding in one of the following languages: C++, Java, Python and/or PHP</li>
<li>2+ years experience of developing, coaching and managing engineering leaders</li>
<li>Demonstrated experience recruiting and managing technical teams, including performance management</li>
<li>BA/BS in Computer Science (In lieu of degree, 4+ years work experience)</li>
</ol>
Public Compensation:
$213,000/year to $293,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at <a href="#">accommodations-ext@fb.com</a>.
#J-18808-Ljbffr

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Principal Machine Learning Software Engineer Job Description As a Machine Learning Engineer specializing in low-level performance optimization, you will play a critical role in helping our customers to advance AMD-based machine learning infrastructure and ensuring the efficient deployment of state-of-the-art large models. You will be part of a dynamic team working on groundbreaking projects and will be responsible for optimizing model execution, including GPU kernels, both for inference and training, in a multi-GPU and multi-node environment. Your contributions will directly impact our ability to deliver cutting-edge AI solutions efficiently and at scale. Key Responsibilities GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize the computational efficiency and reduce execution time while ensuring model accuracy. Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources. Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization. Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques. Model Quantization: Explore and apply model quantization techniques to reduce memory and computation overhead, especially for edge and cloud deployment. Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria. Collaboration: Collaborate closely with machine learning researchers, software engineers, and infrastructure teams to integrate optimized kernels and solutions into production systems. Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code. Qualifications A Bachelor, Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field or equivalent practical experience. Solid understanding of GPU accelerators like ONNX, DeepSpeed, VLLM Strong experience in low-level GPU kernel optimization. Proficiency in CUDA and GPU programming. Experience with distributed computing and multi-GPU environments. Proficiency in performance profiling and optimization tools. Solid programming skills in Python and/or C++. Experience with deep learning frameworks (e.g., JAX, PyTorch, TensorFlow). Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. Additional locations: Santa Clara, Austin, Remote LI-RL1 HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD's Employee Stock Purchase Plan. You'll also be eligible for competitive benefits described in more detail here. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

Machine Learning Software Engineering Manager Apply to this job Location pin icon Bellevue, WA •Menlo Park, CA •Seattle, WA •Burlingame, CA •New York, NY + 4 more - Hide Apply to this job Meta is in search of the world's most creative and experienced engineering leaders. We embrace entrepreneurs as well as those who come from more established organizations. Machine Learning Engineering Managers are clearly characterized by progressive technical experience and demonstrated progression in management responsibility. Machine Learning Software Engineering Manager Responsibilities <ul><li>Be both highly technical and an effective people manager </li><li>Be a subject matter expert in an ML domain </li><li>Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area </li><li>Work with your team and cross functional partners to define and influence strategy </li><li>Drive roadmap creation and execution </li><li>Collaborate with various functions, drive engineering initiatives and have an impact at an organizational level </li><li>Participate in technical design </li><li>Measure the impact of your team and set clear expectations and goals </li><li>Work effectively with cross functional partners and stakeholders to set and achieve optimal outcomes </li></ul>Minimum Qualifications <ul><li>8+ years of software engineering work experience, including hands-on technical management building large scale systems, algorithms, and toolsets within the Machine Learning domain </li><li>8+ years experience coding in one of the following languages: C++, Java, Python and/or PHP </li><li>2+ years experience of developing, coaching and managing engineering leaders </li><li>Demonstrated experience recruiting and managing technical teams, including performance management </li><li>BA/BS in Computer Science (In lieu of degree, 4+ years work experience) </li></ul> For those who live in or expect to work from California if hired for this position, please click here for additional information. Start preparing Learn about how to prepare for your interview with our interview guide, tips, and interactive experiences. Visit interview prep Locations 2 2 Use ctrl + scroll to zoom the map Zoom in Zoom out Recenter Data Center About Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics. $213,000/year to $293,000/year + bonus + equity + benefits Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta. Equal Employment Opportunity and Affirmative Action Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here . Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to accommodations-ext@fb.com .

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Principal Machine Learning Software Engineer Job Description As a Machine Learning Engineer specializing in low-level performance optimization, you will play a critical role in helping our customers to advance AMD-based machine learning infrastructure and ensuring the efficient deployment of state-of-the-art large models. You will be part of a dynamic team working on groundbreaking projects and will be responsible for optimizing model execution, including GPU kernels, both for inference and training, in a multi-GPU and multi-node environment. Your contributions will directly impact our ability to deliver cutting-edge AI solutions efficiently and at scale. Key Responsibilities GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize the computational efficiency and reduce execution time while ensuring model accuracy. Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources. Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization. Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques. Model Quantization: Explore and apply model quantization techniques to reduce memory and computation overhead, especially for edge and cloud deployment. Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria. Collaboration: Collaborate closely with machine learning researchers, software engineers, and infrastructure teams to integrate optimized kernels and solutions into production systems. Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code. Qualifications A Bachelor, Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field or equivalent practical experience. Solid understanding of GPU accelerators like ONNX, DeepSpeed, VLLM Strong experience in low-level GPU kernel optimization. Proficiency in CUDA and GPU programming. Experience with distributed computing and multi-GPU environments. Proficiency in performance profiling and optimization tools. Solid programming skills in Python and/or C++. Experience with deep learning frameworks (e.g., JAX, PyTorch, TensorFlow). Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. Additional locations: Santa Clara, Austin, Remote LI-RL1 HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. Principal Machine Learning Software Engineer Job Description As a Machine Learning Engineer specializing in low-level performance optimization, you will play a critical role in helping our customers to advance AMD-based machine learning infrastructure and ensuring the efficient deployment of state-of-the-art large models. You will be part of a dynamic team working on groundbreaking projects and will be responsible for optimizing model execution, including GPU kernels, both for inference and training, in a multi-GPU and multi-node environment. Your contributions will directly impact our ability to deliver cutting-edge AI solutions efficiently and at scale. Key Responsibilities GPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize the computational efficiency and reduce execution time while ensuring model accuracy. Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources. Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization. Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques. Model Quantization: Explore and apply model quantization techniques to reduce memory and computation overhead, especially for edge and cloud deployment. Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria. Collaboration: Collaborate closely with machine learning researchers, software engineers, and infrastructure teams to integrate optimized kernels and solutions into production systems. Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code. Qualifications A Bachelor, Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field or equivalent practical experience. Solid understanding of GPU accelerators like ONNX, DeepSpeed, VLLM Strong experience in low-level GPU kernel optimization. Proficiency in CUDA and GPU programming. Experience with distributed computing and multi-GPU environments. Proficiency in performance profiling and optimization tools. Solid programming skills in Python and/or C++. Experience with deep learning frameworks (e.g., JAX, PyTorch, TensorFlow). Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. Additional locations: Santa Clara, Austin, Remote LI-RL1 HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. Tags: No, USD $198,100.00/Yr., USD $283,000.00/Yr., US Careers (External)

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ Principal Machine Learning Software Engineer Job Description As a Machine Learning Engineer specializing in low-level performance optimization, you will play a critical role in helping our customers to advance AMD-based machine learning infrastructure and ensuring the efficient deployment of state-of-the-art large models. You will be part of a dynamic team working on groundbreaking projects and will be responsible for optimizing model execution, including GPU kernels, both for inference and training, in a multi-GPU and multi-node environment. Your contributions will directly impact our ability to deliver cutting-edge AI solutions efficiently and at scale. Key ResponsibilitiesGPU Kernel Optimization: Develop and optimize low-level GPU kernels to accelerate inference and training of large machine learning models. Maximize the computational efficiency and reduce execution time while ensuring model accuracy. Multi-GPU and Multi-Node Optimization: Design and implement strategies for distributed model training and inference across multiple GPUs and nodes. Address data parallelism and model parallelism challenges to fully utilize available resources. Performance Profiling: Profile and analyze system and application performance to identify bottlenecks and areas for improvement. Use profiling tools to understand and optimize hardware resource utilization. Parallel Computing: Leverage parallel computing techniques to improve the scalability and performance of machine learning workloads. Implement multi-threading and GPU synchronization techniques. Model Quantization: Explore and apply model quantization techniques to reduce memory and computation overhead, especially for edge and cloud deployment. Benchmarking and Testing: Develop benchmarks and testing procedures to assess the performance and stability of optimized models and frameworks. Ensure that the solutions meet or exceed the defined performance criteria. Collaboration: Collaborate closely with machine learning researchers, software engineers, and infrastructure teams to integrate optimized kernels and solutions into production systems. Documentation: Create detailed documentation of optimizations, best practices, and implementation guidelines to facilitate knowledge sharing and maintainable code. Qualifications A Bachelor, Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field or equivalent practical experience. Solid understanding of GPU accelerators like ONNX, DeepSpeed, VLLM Strong experience in low-level GPU kernel optimization. Proficiency in CUDA and GPU programming. Experience with distributed computing and multi-GPU environments. Proficiency in performance profiling and optimization tools. Solid programming skills in Python and/or C++. Experience with deep learning frameworks (e.g., JAX, PyTorch, TensorFlow). Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. LI-RL1 At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employe

Summary: Facebook is seeking a data center Critical Facility Engineer to join our Data Center Facility Operations team. Our data centers serve as the foundation upon which our software operates to meet the demands of our customers. The Critical Facility Engineer will be a part of the Facility Operations team responsible for operating and maintaining critical systems in our data centers. The candidate will need to be experienced in diverse industries such as electrical generation, electrical distribution, cooling technologies and fire protection systems. Required Skills: Critical Facility Engineer Responsibilities: Perform hands-on operations and maintenance which includes all physical and administrative operations tasks, service, and maintenance in accordance with site processes and procedures to ensure the highest levels of uptime, efficiency, and safety without disruption to the business Complete work order requests accurately and on time Maintain a positive and professional working relationship with cross functional teams Respond quickly, using Facebook procedures or emergency operating procedures to data center facility emergencies Regularly inspect equipment, buildings, safety routes and grounds to check or identify any abnormal or unsafe conditions or faults Troubleshoot, evaluate and recommend system upgrades Order parts and supplies for maintenance and repairs Work with vendors and contractors to ensure work is in accordance with the agreed Facebook processes, procedures, and standards Escalate issues to facility management appropriately and timely Assist in scheduling and supervising vendors/subcontractors during equipment/systems maintenance and service Provides technical expertise and assistance as required Provides recommendation of improvements to the operations and maintenance program on an on-going basis Ability to work night shift work and set shift which may include nights and holidays Minimum Qualifications: Minimum Qualifications: High school diploma or equivalent (i.e. GED) 5+ years experience in electrical, HVAC, mechanical, controls, or other technical maintenance field Associate's degree in engineering plus 3+ years experience or Bachelor's degree in related field plus 2+ years experience in electrical, HVAC, mechanical, or controls will be considered in lieu of 5+ years experience Knowledge of Microsoft Office Suite - Word, Excel and Outlook Experience interpreting blueprints/CAD drawings Regularly walk job site areas of flat and uneven terrain Work at varying heights and from ladders Use hands and fingers Reach/push/pull with hands/arms/shoulders Stoop, kneel, crouch and crawl May lift and/or otherwise move 45 pounds or more Preferred Qualifications: Preferred Qualifications: 3+ years experience in a data center or other Critical Environment (pharma, clean room, medical, power production, etc.) Trade Certification or state license in Electrical or Mechanical (HVAC) Professional affiliations (7x24 Exchange, IFMA, Data Center Pulse, etc.) Knowledge of CMMS systems Knowledge of critical facilities operations Knowledge of mechanical, electrical, and life safety monitoring and control systems typically used in critical environments Industry: Internet Equal Opportunity: Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at .

Machine Learning Software Engineer Jobs in Bellevue, WA

Principal Machine Learning Software Engineer
December 10, 2024

Machine Learning Software Engineering Manager
December 8, 2024

Principal Machine Learning Software Engineer
December 6, 2024

Machine Learning Software Engineering Manager
December 1, 2024

Principal Machine Learning Software Engineer
November 30, 2024

Principal Machine Learning Software Engineer
November 30, 2024

Machine Learning Software Engineering Manager
November 28, 2024

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Top companies

Machine Learning Software Engineer Jobs in Bellevue, WA

Principal Machine Learning Software EngineerDecember 10, 2024

Machine Learning Software Engineering ManagerDecember 8, 2024

Principal Machine Learning Software EngineerDecember 6, 2024

Machine Learning Software Engineering ManagerDecember 1, 2024

Principal Machine Learning Software EngineerNovember 30, 2024

Principal Machine Learning Software EngineerNovember 30, 2024

Machine Learning Software Engineering ManagerNovember 28, 2024

Quick filters

Top companies

Principal Machine Learning Software Engineer
December 10, 2024

Machine Learning Software Engineering Manager
December 8, 2024

Principal Machine Learning Software Engineer
December 6, 2024

Machine Learning Software Engineering Manager
December 1, 2024

Principal Machine Learning Software Engineer
November 30, 2024

Principal Machine Learning Software Engineer
November 30, 2024

Machine Learning Software Engineering Manager
November 28, 2024