3,479 Machine Learning jobs in the United States

Machine Learning Engineer at Exact Sciences summary:

The Machine Learning Engineer at Exact Sciences applies advanced AI and machine learning techniques to analyze biological, genomic, clinical, and healthcare data to support cancer screening and precision oncology. They collaborate with biostatisticians, bioinformatics scientists, and data scientists to design, implement, and deploy innovative AI solutions that improve cancer detection, prevention, and treatment. This role involves continuous learning, strategic contribution to AI methodologies, and working within an agile framework to accelerate research and clinical insights.

Help us change lives

At Exact Sciences, we’re helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you’re working to help others.

Position Overview

The Machine Learning Engineer, with moderate guidance from more experienced engineers, works individually and in collaboration with others on multiple projects which are moderate to complex in scope. This role utilizes working knowledge of advanced artificial intelligence and machine learning algorithms and models to solve problems involving biological, genomic, clinical and healthcare data within a setting of advanced cancer screening and precision oncology. This role is involved at every step of the solution development process, from ideation, design, implementation and deployment. This position contributes to the strategic vision for the application of cutting-edge AI methodologies at Exact Sciences and works as a partner with biostatisticians, bioinformatics scientists, and data scientists to further our goal of helping eradicate cancer by preventing it, detecting it earlier, and guiding personalized treatment.

Essential Duties

Include, but are not limited to, the following:

• Keep up with external and internal advances in AI technology.
• Collaborate with other ML/AI engineers and relevant partners to articulate “AI affordance”: what do the advances in AI technology allow us to do (or do more efficiently or effectively) that we couldn’t do before?
• Work with stakeholders to discover requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications.
• Collaborate with other ML/AI engineers and relevant partners to contribute to the design of software solutions that utilize state-of-the art artificial intelligence and machine learning techniques.
• Work with other AI and ML engineers and software engineers and contribute to the implementation and deployment of ML and AI solutions.
• Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions.
• Contribute to the execution of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes.
• Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them.
• Exercise judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results.
• Ability to clearly communicate, and to explain basic to intermediate topics to audiences of peers.
• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
• Support and comply with the company’s Quality Management System policies and procedures.
• Maintain regular and reliable attendance.
• Ability to act with an inclusion mindset and model these behaviors for the organization.
• Ability to work designated schedule.
• Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day.
• Ability to travel 5% of working time away from work location, may include overnight/weekend travel

Minimum Qualifications

• Ph.D.  in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, or master’s degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of experience in lieu of a Ph.D.
• Demonstrated knowledge of advanced AI concepts, such as artificial neural networks, deep learning, and reinforcement learning.
• Demonstrated knowledge of artificial intelligence and machine learning techniques within one or more of the following fields: natural language processing, image processing and computer vision, image and pattern recognition.
• Demonstrated knowledge of large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
• Programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow, PyTorch, or SKLearn.
• Knowledge of open-source AI models.
• Demonstrated ability to perform the essential duties of the position with or without accommodation.
• Authorization to work in the United States without sponsorship.

Preferred Qualifications

• 1+ years of life sciences industry experience working with biological data.
• 1+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
• Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
• Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.
• Scientific understanding of cancer biology

Salary Range:

Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.

Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.

Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.

To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.

Keywords:

machine learning, artificial intelligence, bioinformatics, cancer diagnostics, precision oncology, deep learning, data science, healthcare data, Python, TensorFlow, AI deployment

Machine Learning Engineer at Exact Sciences summary:

The Machine Learning Engineer at Exact Sciences applies advanced AI and machine learning techniques to analyze biological, genomic, clinical, and healthcare data to support cancer screening and precision oncology. They collaborate with biostatisticians, bioinformatics scientists, and data scientists to design, implement, and deploy innovative AI solutions that improve cancer detection, prevention, and treatment. This role involves continuous learning, strategic contribution to AI methodologies, and working within an agile framework to accelerate research and clinical insights.

Help us change lives

At Exact Sciences, we’re helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you’re working to help others.

Position Overview

The Machine Learning Engineer, with moderate guidance from more experienced engineers, works individually and in collaboration with others on multiple projects which are moderate to complex in scope. This role utilizes working knowledge of advanced artificial intelligence and machine learning algorithms and models to solve problems involving biological, genomic, clinical and healthcare data within a setting of advanced cancer screening and precision oncology. This role is involved at every step of the solution development process, from ideation, design, implementation and deployment. This position contributes to the strategic vision for the application of cutting-edge AI methodologies at Exact Sciences and works as a partner with biostatisticians, bioinformatics scientists, and data scientists to further our goal of helping eradicate cancer by preventing it, detecting it earlier, and guiding personalized treatment.

Essential Duties

Include, but are not limited to, the following:

• Keep up with external and internal advances in AI technology.
• Collaborate with other ML/AI engineers and relevant partners to articulate “AI affordance”: what do the advances in AI technology allow us to do (or do more efficiently or effectively) that we couldn’t do before?
• Work with stakeholders to discover requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications.
• Collaborate with other ML/AI engineers and relevant partners to contribute to the design of software solutions that utilize state-of-the art artificial intelligence and machine learning techniques.
• Work with other AI and ML engineers and software engineers and contribute to the implementation and deployment of ML and AI solutions.
• Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions.
• Contribute to the execution of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes.
• Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them.
• Exercise judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results.
• Ability to clearly communicate, and to explain basic to intermediate topics to audiences of peers.
• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
• Support and comply with the company’s Quality Management System policies and procedures.
• Maintain regular and reliable attendance.
• Ability to act with an inclusion mindset and model these behaviors for the organization.
• Ability to work designated schedule.
• Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day.
• Ability to travel 5% of working time away from work location, may include overnight/weekend travel

Minimum Qualifications

• Ph.D.  in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, or master’s degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of experience in lieu of a Ph.D.
• Demonstrated knowledge of advanced AI concepts, such as artificial neural networks, deep learning, and reinforcement learning.
• Demonstrated knowledge of artificial intelligence and machine learning techniques within one or more of the following fields: natural language processing, image processing and computer vision, image and pattern recognition.
• Demonstrated knowledge of large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
• Programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow, PyTorch, or SKLearn.
• Knowledge of open-source AI models.
• Demonstrated ability to perform the essential duties of the position with or without accommodation.
• Authorization to work in the United States without sponsorship.

Preferred Qualifications

• 1+ years of life sciences industry experience working with biological data.
• 1+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
• Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
• Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.
• Scientific understanding of cancer biology

Salary Range:

Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.

Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.

Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.

To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.

Keywords:

machine learning, artificial intelligence, bioinformatics, cancer diagnostics, precision oncology, deep learning, data science, healthcare data, Python, TensorFlow, AI deployment

Lead Machine Learning

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team building models and productionizing machine learning applications and systems at scale providing Kafka infrastructure to support an event-driven architecture, developing DevOps best practices and the development of tools to facilitate cloud-based application development. 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.

• Will Guide early-career engineers by providing learning tasks as well as work-related tasks, directs the work of emerging talent, and helps them continue to grow in their technical skillset through mentorship.

• Operate independently, investigate solutions deeply, and see a task through from planning and design to deployment and adoption.

• Switch work priorities as new initiatives emerge, embrace change, and effectively communicate complex ideas while actively listening to feedback.

• Use critical thinking to question assumptions and improve processes, and has a passion for learning new technologies, creating proof-of-concepts, and educating others.

Basic 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 Java

• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

• 3+ 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 code

• 2+ years of experience with data gathering and preparation for ML models

• 2+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation

• 2 + years experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

• 2 + Years Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
  2+ years experience with event driven architecture such as Kafka

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer)

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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 or via email at . 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

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).

Interview Process: Onsite Interview at Davie, FL

JOB SUMMARY:

We are seeking a dynamic and technically skilled Engineering Maintenance Technician IIto lead and support cross-functional initiatives across IT, OT, and controls systems in a GMP-regulated pharmaceutical manufacturing environment. This role will drive digital transformation through AI integration, Power Platform development, and advanced automation technologies, ensuring compliance, efficiency, and innovation. The Automation Engineer will also provide troubleshooting support for operational equipment, facilities, and innovation activities.

Key Responsibilities:

Automation Systems Design & Integration

Develop, configure, and maintain automation systems including PLC, SCADA, MES, and DCS platforms.

Interface automation systems with enterprise IT tools and data platforms (e.g., SAP, OSIsoft PI, Seeq, Solvae, MES, various historians).

Digital Transformation & AI Enablement

Apply AI/ML models for predictive maintenance, anomaly detection, and process optimization using tools like Python, TensorFlow, and Power BI Fabric.

Collaborate with data engineers/data scientists to integrate sensor data and batch records into centralized analytics platforms.

Power Platform Development

Build and deploy low-code applications using Power Apps, Power Automate, and Power BI to digitize workflows and enhance productivity.

Use Copilot and Power Fx to simplify app creation and automate repetitive tasks.

Validation & Compliance

Ensure systems meet GxP, FDA, and ISO standards through robust Computer Systems Validation (CSV) and documentation practices.

Cross-Functional Collaboration

Work closely with engineering, IT, quality, and manufacturing teams to align automation strategies with business goals.

Support training and change management initiatives to drive adoption of digital tools.

Required Qualifications:

• Master’s or Ph.D. in Electrical Engineering, Computer Science, Automation, Robotics, or related field (Ph.D. with less experience acceptable).
• Recent graduate within the last 3 years with 3+ years of automation/AI/OT/controls experience in a GMP-regulated pharmaceutical or medical device environment.
• Proficiency in PLC programming (Allen-Bradley, Siemens), SCADA, and industrial networking.
• Strong command of Python, Power Platform, and AI/ML frameworks.
• Familiarity with digital twins, robotic systems, and smart manufacturing equipment.

Preferred Qualifications:

• Experience with Industry 4.0/Pharma 4.0 technologies and principles.
• Knowledge of ISA standards (e.g., ISA 18.2 for alarm rationalization).
• Ability to interpret and apply AI/ML models to manufacturing data.
• Strong documentation, problem-solving, and communication skills.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.