<h3><strong>Machine Learning Engineer</strong></h3>
<p>We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity to shape and create our machine learning capabilities from the ground up. You'll be at the forefront of innovation, designing and implementing ML systems that drive our business forward.</p>
<h3><strong>Responsibilities:</strong></h3>
<ul><li>Design, develop, and implement machine learning models and algorithms</li><li>Analyze large datasets and extract meaningful insights</li><li>Collaborate with cross-functional teams to integrate ML solutions into existing systems</li><li>Optimize ML models for performance and scalability</li><li>Stay current with the latest advancements in machine learning and AI</li><li>Create and implement big data processing pipelines and architectures</li><li>Design and build scalable data infrastructure to support ML applications</li></ul>
<h3><strong>Requirements:</strong></h3>
<ul><li>Bachelor's or Master's degree in Computer Science, Data Science, or related field</li><li>3+ years of experience in machine learning or AI development</li><li>Strong proficiency in Python and its ML/data science libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas)</li><li>Solid understanding of machine learning algorithms and statistical modeling</li><li>Experience with big data technologies (e.g., Hadoop, Spark, Kafka)</li><li>Proven ability to create and implement big data solutions from scratch</li><li>Comfortable setting up and managing distributed computing environments</li><li>Experience in designing and implementing data pipelines for large-scale data processing</li><li>Proficient in working with various database systems, both SQL and NoSQL, depending on the use case</li><li>Strong skills in data modeling and database design for machine learning applications</li><li>Excellent problem-solving and analytical skills</li><li>Strong communication skills and ability to work in a team environment</li></ul>
<h3><strong>Preferred Qualifications:</strong></h3>
<ul><li>Experience in creating and managing real-time data streaming architectures</li><li>AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty</li><li>Experience with AWS machine learning services</li><li>Proficiency in using AWS big data services</li><li>Knowledge of serverless architectures on AWS (e.g., Lambda)</li><li>Experience in creating and managing real-time data streaming architectures on AWS (e.g., Kinesis)</li><li>Understanding of AWS security best practices for machine learning and data processing workflows</li></ul>
<h3><strong>What you’ll do day-to-day:</strong></h3>
<ul><li>Be a member of a world-class team focused on inventing solutions that have the ability to impact the world</li><li>Tackle a wide variety of technical problems throughout the stack and contribute daily to all parts of our product code base</li><li>Help build a beautiful, intuitive product that revolutionizes the nonprofit industry</li><li>Work closely with our customers, founders, team members and Board to understand customer pain points, develop solutions, and prototype, iterate, and deploy code on regular cycles</li></ul>
#J-18808-Ljbffr

Towers Crescent (12066), United States of America, Vienna, VirginiaSenior Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you''ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You''ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You''ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You''ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Team Info:In the Center for Machine Learning Feature Platform team, we are building and deploying core capabilities to enable data scientists and analysts to consistently and repeatedly deliver machine learning models and analytical reports. We are currently working to enable the On-Demand real-time, Feature Library workstream leveraging distributed compute, streaming data, containers, Python/Scala/Java, and AWS serverless technologies like Lambda, DynamoDB, Neptune, and Kinesis Data Analytics.What you''ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you''ll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production.Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications:Bachelor''s degree. At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications:Master''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience with container ecosystem technologies such as Docker or Kubernetes 2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization for this position.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City''s Fair Chance Act; Philadelphia''s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [Click Here to Email Your Resum]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One''s recruiting process, please send an email to [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

<p>Machine Learning Engineer
We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity to shape and create our machine learning capabilities from the ground up. You'll be at the forefront of innovation, designing and implementing ML systems that drive our business forward.

Responsibilities:
Design, develop, and implement machine learning models and algorithms
Analyze large datasets and extract meaningful insights
Collaborate with cross-functional teams to integrate ML solutions into existing systems
Optimize ML models for performance and scalability
Stay current with the latest advancements in machine learning and AI
Create and implement big data processing pipelines and architectures
Design and build scalable data infrastructure to support ML applications

Requirements:
Bachelor's or Master's degree in Computer Science, Data Science, or related field
3+ years of experience in machine learning or AI development
Strong proficiency in Python and its ML/data science libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas)
Solid understanding of machine learning algorithms and statistical modeling
Experience with big data technologies (e.g., Hadoop, Spark, Kafka)
Proven ability to create and implement big data solutions from scratch
Comfortable setting up and managing distributed computing environments
Experience in designing and implementing data pipelines for large-scale data processing
Proficient in working with various database systems, both SQL and NoSQL, depending on the use case
Strong skills in data modeling and database design for machine learning applications
Excellent problem-solving and analytical skills
Strong communication skills and ability to work in a team environment

Preferred Qualifications:
Experience in creating and managing real-time data streaming architectures
AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty
Experience with AWS machine learning services
Proficiency in using AWS big data services
Knowledge of serverless architectures on AWS (e.g., Lambda)
Experience in creating and managing real-time data streaming architectures on AWS (e.g., Kinesis)
Understanding of AWS security best practices for machine learning and data processing workflows

What you’ll do day-to-day:
Be a member of a world-class team focused on inventing solutions that have the ability to impact the world
Tackle a wide variety of technical problems throughout the stack and contribute daily to all parts of our product code base
Help build a beautiful, intuitive product that revolutionizes the nonprofit industry
Work closely with our customers, founders, team members and Board to understand customer pain points, develop solutions, and prototype, iterate, and deploy code on regular cycles

#J-18808-Ljbffr</p>

<p>Towers Crescent (12066), United States of America, Vienna, VirginiaSenior Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you''ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You''ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You''ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You''ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Team Info:In the Center for Machine Learning Feature Platform team, we are building and deploying core capabilities to enable data scientists and analysts to consistently and repeatedly deliver machine learning models and analytical reports. We are currently working to enable the On-Demand real-time, Feature Library workstream leveraging distributed compute, streaming data, containers, Python/Scala/Java, and AWS serverless technologies like Lambda, DynamoDB, Neptune, and Kinesis Data Analytics.What you''ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you''ll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production.Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications:Bachelor''s degree. At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications:Master''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience with container ecosystem technologies such as Docker or Kubernetes 2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization for this position.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City''s Fair Chance Act; Philadelphia''s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [Click Here to Email Your Resum]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One''s recruiting process, please send an email to [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p>

<p>77 West Wacker Dr (35012), United States of America, Chicago, IllinoisSenior Lead Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you''ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You''ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You''ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You''ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you''ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you''ll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production.Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Capital One is open to hiring a Remote Employee for this opportunity.Basic Qualifications:Bachelor''s degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systemsAt least 2 years of experience leading teams developing ML solutions Preferred Qualifications:Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code3+ years of experience with data gathering and preparation for ML models3+ years of technical leadership experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences At this time, Capital One will not sponsor a new applicant for employment authorization for this position.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City''s Fair Chance Act; Philadelphia''s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [Click Here to Email Your Resum]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One''s recruiting process, please send an email to [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p>

<p>Center 1 (19052), United States of America, McLean, VirginiaLead Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you''ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You''ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You''ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You''ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you''ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you''ll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production.Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Capital One is open to hiring a Remote Employee for this opportunityBasic Qualifications:Bachelor''s degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)At least 4 years of experience programming with Python, Scala, or JavaAt least 2 years of experience building, scaling, and optimizing ML systemsPreferred Qualifications:Master''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code2+ years of experience with data gathering and preparation for ML models2+ years of people leader experience1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud PlatformExperience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization for this position.No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City''s Fair Chance Act; Philadelphia''s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [Click Here to Email Your Resum]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One''s recruiting process, please send an email to [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p>

Machine Learning Engineer Jobs in Newton, MA

Machine Learning Engineer
December 9, 2024

Senior Machine Learning Engineer Remoteeligible
December 3, 2024

Senior Machine Learning Engineer Remoteeligible
December 2, 2024

Machine Learning Engineer
December 2, 2024

Senior Machine Learning Engineer Remoteeligible
December 1, 2024

Senior Lead Machine Learning Engineer Remoteeligible
December 1, 2024

Lead Machine Learning Engineer Remoteeligible
November 30, 2024

Quick filters

Top companies

Machine Learning Engineer Jobs in Newton, MA

Machine Learning EngineerDecember 9, 2024

Senior Machine Learning Engineer RemoteeligibleDecember 3, 2024

Senior Machine Learning Engineer RemoteeligibleDecember 2, 2024

Machine Learning EngineerDecember 2, 2024

Senior Machine Learning Engineer RemoteeligibleDecember 1, 2024

Senior Lead Machine Learning Engineer RemoteeligibleDecember 1, 2024

Lead Machine Learning Engineer RemoteeligibleNovember 30, 2024