General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems. We have an exciting opportunity for a Machine Learning Engineer in Boulder, CO. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions. DUTIES AND RESPONSIBILITIES: Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope. In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope. Lead technical teams and scope challenging projects into executable sprints. Drive code reviews to help team adhere to general DevSecOps and MLOps best practices. Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution. Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience. Interface with external vendors and partners to integrate their technology into the team’s autonomy stack. Maintains the strict confidentiality of sensitive information. Performs other duties as assigned. Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices. We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply. 47055 Job Qualifications: Typically requires a bachelors, masters degree or PhD in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and progressive machine learning engineering experience as follows; five or more years of experience with a bachelors degree or three or more years of experience with a masters degree. May substitute equivalent machine learning engineer experience in lieu of education. Must have an advanced understanding of machine learning concepts, principles, and theory. Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance. Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment. Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience. Must be able to work both independently and on a team. Must have a demonstrated history of applying novel technical solutions in fast evolving product areas. Able to work extended hours as required. Ability to obtain and maintain a DoD security clearance is required. Salary: $116,480 - $208,505 Travel Percentage Required 0 - 25 Relocation Assistance Provided Not Provided US Citizenship Required? Yes Clearance Required? Desired Clearance Level Secret Workstyle Hybrid General Atomics is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity/Affirmative Action Employer and will consider all qualified applicants for employment without regard to race, color, religion, religious creed, ancestry, gender, pregnancy, sex, sexual orientation, transitioning status, gender identity, gender expression, national origin, age, genetic information, military and veteran status, marital status, medical condition, mental disability, physical disability, or any other basis protected by local, state, or federal law. EEO is the law. We also prohibit compensation discrimination under all applicable laws. To learn more visit https://tbcdn.talentbrew.com/company/499/v2_0/EEO Notices.pdf. U.S. Citizenship is required for certain positions.

Your work days are brighter here. At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here. <h3>About the Team </h3>We're working on making machine learning core to Workday's products by building data products and auto-ml models that can be scaled out to hundreds of use cases within Workday. As part of a global, high-growth technology company, our work supports thousands of the largest global companies and more than 30 million end users. You will solve complex problems and influence machine learning and application development across Workday. Our team is passionate about teaching and learning, so be eager to share your expertise and learn from us. Join us as we change the way millions of people work. <h3>About the Role </h3>We're building ML powered Search and Generative AI services and platforms to modernize how users interact with workday - adding ease, intelligence and efficiency to everyday interactions. All of these capabilities are designed to be applied across a wide range of applications within Workday. As a machine learning engineer, you will help develop tailored experiences for every user powered by advanced Large Language Models (LLMs), personalization, and predictive analysis. You will work closely with other ML engineers and software developers to deliver ML solutions that enable ML powered search and user experience across Workday’s product ecosystem. You will apply current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised, deep learning and classical. You will develop new APIs/microservices and deploy them using docker/kubernetes at scale. You will use Workday’s vast computing resources on rich, exclusive datasets to deliver value that transforms the way our customers make decisions and run their business. We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of users. Sound like your kind of challenge? <h3>About You </h3><h3>Key Responsibilities: </h3><ul><li>Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users. </li><li>Preprocess and clean large amounts of unstructured text data to ensure quality and consistency for Natural Language Processing (NLP) and other ML model training. </li><li>Engineer relevant features from textual data to facilitate accurate model predictions and classification. </li><li>Apply machine learning techniques including LLMs, deep learning including generative models, natural language understanding, sentiment analysis, topic modeling, and named entity recognition to analyze large sets of HR-related text data, and design and launch pioneering cloud based machine learning architectures. </li><li>Train, validate, and fine-tune machine learning models using large-scale datasets to achieve robust performance. </li><li>Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products. </li><li>Collaborate across teams to deliver your products through Workday end user applications. </li><li>Be given autonomy and ownership over your work, but with the support of the entire organization. </li><li>Keep abreast of the latest advancements in NLP research, techniques, and tools. </li><li>Have extraordinary opportunities for career growth and learning in a fast-growing, forward-looking company. </li> </ul><h3>Basic Qualifications: </h3><ul><li>Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, math or equivalent. </li><li>6 or more years of experience developing, deploying, and supporting high-performance systems in production. </li><li>6 or more years of experience with industry tools used to build scalable machine learning systems, such as AWS, SQL, Elasticsearch/Open Search, Kubernetes, Docker and/or Spark. </li><li>6 or more years of experience delivering applied machine learning products, including taking a product through design, implementation, and to production. </li><li>6 or more years of developing Machine Learning driven features with Python (including NumPy, SciPy, Pandas), JVM, and Linux. </li><li>Proven theoretical and practical understanding of statistical analysis and machine learning algorithms, natural language processing, especially for supervised, unsupervised and self-supervised methods. </li><li>Experience with generative models, large language models, and transformer based deep neural networks. </li> </ul><h3>Other Qualifications: </h3><ul><li>Experience with data engineering and data wrangling using e.g. Pandas and PySpark. </li><li>Familiarity with LLMs such as Llama, different GPT models, and their applications in real-world scenarios. </li><li>Exposure to advanced techniques such as reinforcement learning, imitation learning, and graph neural networks. </li><li>Experience with cloud computing platforms (e.g. AWS, GCP) and containerization technologies (e.g. Docker). </li><li>Standout colleague, strong communication skills, with experience working across functions and teams. </li><li>Bonus points for relevant PhD and/or machine learning related research publications. </li><li>Resilience to obstacles, and ability to solve problems independently. </li> </ul><h3>Workday Pay Transparency Statement </h3>The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please <a >click here </a>. Primary Location: USA.CO.Boulder Primary Location Base Pay Range: $192,000 USD - $288,000 USD Additional CAN Location(s) Base Pay Range: $173,600 - $260,400 CAD <h3>Our Approach to Flexible Work </h3>With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! #J-18808-Ljbffr

An exciting generative AI startup is growing its machine learning team. We’re hiring a Machine Learning Engineer to work on complex problems with large language models and program synthesis. The founding team has a successful track record. You’ll need to have experience in end-to-end model training, from data curation to architecture and tuning. Industry experience is a must for this role. It would be nice if you had experience with language models and dialogue generation. Python, PyTorch, and TensorFlow are important! <h3>Apply for this job </h3>Name Email Phone Message Files: Drop files here or accepted file types: pdf, doc, Max. file size: 10 MB, Max. files: 3. #J-18808-Ljbffr

Your work days are brighter here. At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That's why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don't need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here. About the Team We're working on making machine learning core to Workday's products by building data products and auto-ml models that can be scaled out to hundreds of use cases within Workday. As part of a global, high-growth technology company, our work supports thousands of the largest global companies and more than 30 million end users. You will solve complex problems and influence machine learning and application development across Workday. Our team is passionate about teaching and learning, so be eager to share your expertise and learn from us. Join us as we change the way millions of people work. About the Role We're building ML powered Search and Generative AI services and platforms to modernize how users interact with workday - adding ease, intelligence and efficiency to everyday interactions. All of these capabilities are designed to be applied across a wide range of applications within Workday. As a machine learning engineer, you will help develop tailored experiences for every user powered by advanced Large Language Models (LLMs), personalization, and predictive analysis. You will work closely with other ML engineers and software developers to deliver ML solutions that enable ML powered search and user experience across Workday's product ecosystem. You will apply current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised, deep learning and classical. You will develop new APIs/microservices and deploy them using docker/kubernetes at scale. You will use Workday's vast computing resources on rich, exclusive datasets to deliver value that transforms the way our customers make decisions and run their business. We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of users. Sound like your kind of challenge? About You Key Responsibilities: <ul> <li>Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users. </li><li>Preprocess and clean large amounts of unstructured text data to ensure quality and consistency for Natural Language Processing (NLP) and other ML model training. </li><li>Engineer relevant features from textual data to facilitate accurate model predictions and classification. </li><li>Apply machine learning techniques including LLMs, deep learning including generative models, natural language understanding, sentiment analysis, topic modeling, and named entity recognition to analyze large sets of HR-related text data, and design and launch pioneering cloud based machine learning architectures. </li><li>Train, validate, and fine-tune machine learning models using large-scale datasets to achieve robust performance. </li><li>Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products. </li><li>Collaborate across teams to deliver your products through Workday end user applications. </li><li>Be given autonomy and ownership over your work, but with the support of the entire organization. </li><li>Keep abreast of the latest advancements in NLP research, techniques, and tools. </li><li>Have extraordinary opportunities for career growth and learning in a fast-growing, forward-looking company. </li></ul>Basic Qualifications: <ul> <li>Bachelor's (Master's preferred) degree in engineering, computer science, physics, math or equivalent. </li><li>6 or more years of experience developing, deploying, and supporting high-performance systems in production </li><li>6 or more years of experience with industry tools used to build scalable machine learning systems, such as AWS, SQL, Elasticsearch/Open Search, Kubernetes, Docker and/or Spark </li><li>6 or more years of experience delivering applied machine learning products, including taking a product through design, implementation, and to production </li><li>6 or more years of developing Machine Learning driven features with Python (including NumPy, SciPy, Pandas), JVM, and Linux </li><li>Proven theoretical and practical understanding of statistical analysis and machine learning algorithms, natural language processing, especially for supervised, unsupervised and self-supervised methods. </li><li>Experience with generative models, large language models, and transformer based deep neural networks. </li></ul>Other Qualifications: <ul> <li>Experience with data engineering and data wrangling using e.g. Pandas and PySpark. </li><li>Familiarity with LLMs such as Llama, different GPT models, and their applications in real-world scenarios. </li><li>Exposure to advanced techniques such as reinforcement learning, imitation learning, and graph neural networks. </li><li>Experience with cloud computing platforms (e.g. AWS, GCP) and containerization technologies (e.g. Docker). </li><li>Standout colleague, strong communication skills, with experience working across functions and teams. </li><li>Bonus points for relevant PhD and/or machine learning related research publications. </li><li>Resilience to obstacles, and ability to solve problems independently. </li></ul> Posting End Date: 11/18/24 The application deadline for this role is the same as the posting end date stated. Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here. Primary Location: USA.CO.Boulder Primary Location Base Pay Range: $192,000 USD - $288,000 USD Additional CAN Location(s) Base Pay Range: $173,600 - $260,400 CAD Our Approach to Flexible Work With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

Machine Learning Engineer Jobs in Boulder, CO

Senior Machine Learning Engineer
December 10, 2024

Principal Machine Learning Engineer
December 9, 2024

Machine Learning Engineer Nlp
December 9, 2024

Principal Machine Learning Engineer
December 1, 2024

Senior Machine Learning Engineer
November 29, 2024

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Machine Learning Engineer Jobs in Boulder, CO

Senior Machine Learning EngineerDecember 10, 2024

Principal Machine Learning EngineerDecember 9, 2024

Machine Learning Engineer NlpDecember 9, 2024

Principal Machine Learning EngineerDecember 1, 2024

Senior Machine Learning EngineerNovember 29, 2024