AI ML Engineering Jobs
AI ML Engineering jobs are open across technology, healthcare, finance, and manufacturing, at every level from new-grad to principal and staff, with specializations in deep learning, natural language processing, and computer vision. Find a role that fits from the openings below and apply directly.
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Showing 5 of 4,100+ AI ML Engineering jobs
INTRODUCTION
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
ROLE AND RESPONSIBILITIES
As a Director of AI/ML Engineering within our team, you will lead a highly skilled engineering team focused on building, deploying, and scaling robust AI and machine learning systems. You will collaborate with cross-functional partners to drive strategic innovation, implement modern MLOps pipelines, and deliver high-impact AI capabilities that directly improve health outcomes. In this role, you will have the opportunity to leverage cutting-edge technologies, design scalable architectures, and shape the future of healthcare technology on an enterprise scale.
You'll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. This position follows a hybrid schedule with four in-office days per week.
Primary Responsibilities:
- Provide strategic direction and technical leadership for the AI/ML engineering team, strategically using AI to solve complex business problems, unlock new opportunities, and deliver tangible business value
- Manage, mentor, and grow a high-performing team of AI/ML engineers, aligning hiring with technical and AI competencies, setting clear developmental goals, and actively removing barriers to accelerate adoption
- Champion AI as a core driver of team success, proactively shaping how AI models and systems are developed, deployed, and utilized across the organization
- Champion the ethical use of AI by embedding transparency, fairness, accountability, and robust governance throughout the entire AI/ML system lifecycle
- Drive the design, architecture, and deployment of scalable, production-grade AI/ML pipelines and modern MLOps practices, including automated testing, continuous integration/deployment (CI/CD), and model monitoring
- Collaborate with data science, product, and business partners to translate cutting-edge AI advancements and business opportunities into reliable, production-ready capabilities
- Standardize engineering practices across the team, ensuring high code quality, system performance, and integration with robust security protocols
- Evaluate emerging AI/ML technologies, tools, and methodologies to drive continuous innovation and streamline engineering workflows
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
BASIC QUALIFICATIONS
- 9+ years of software engineering experience
- 5+ years of experience leading, managing, or mentoring technical engineering teams (direct people management or lead architect/delivery lead experience)
- 4+ years of hands-on experience designing, building, and deploying AI/ML solutions, including LLMs, Generative AI, and traditional ML models
- 3+ years of experience with MLOps practices, including ML pipeline orchestration, model monitoring, and automated deployment (CI/CD)
- 3+ years of experience working with major cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes)
- 3+ years of experience with security, access controls, logging, monitoring, performance tuning, disaster recovery, and production operations
PREFERRED QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent experience)
- Experience in healthcare or another highly regulated industry
- Experience implementing Responsible AI frameworks, AI safety protocols, and governance standards
- Proven excellent communication and stakeholder management skills, with the ability to articulate complex technical concepts to non-technical business leaders
- Solid proficiency in programming languages such as Python, PyTorch, TensorFlow, or other modern ML frameworks
All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
COMPENSATION
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $176,700 - $302,900 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.
INTRODUCTION
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
ROLE AND RESPONSIBILITIES
As a Director of AI/ML Engineering within our team, you will lead a highly skilled engineering team focused on building, deploying, and scaling robust AI and machine learning systems. You will collaborate with cross-functional partners to drive strategic innovation, implement modern MLOps pipelines, and deliver high-impact AI capabilities that directly improve health outcomes. In this role, you will have the opportunity to leverage cutting-edge technologies, design scalable architectures, and shape the future of healthcare technology on an enterprise scale.
You'll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. This position follows a hybrid schedule with four in-office days per week.
Primary Responsibilities:
- Provide strategic direction and technical leadership for the AI/ML engineering team, strategically using AI to solve complex business problems, unlock new opportunities, and deliver tangible business value
- Manage, mentor, and grow a high-performing team of AI/ML engineers, aligning hiring with technical and AI competencies, setting clear developmental goals, and actively removing barriers to accelerate adoption
- Champion AI as a core driver of team success, proactively shaping how AI models and systems are developed, deployed, and utilized across the organization
- Champion the ethical use of AI by embedding transparency, fairness, accountability, and robust governance throughout the entire AI/ML system lifecycle
- Drive the design, architecture, and deployment of scalable, production-grade AI/ML pipelines and modern MLOps practices, including automated testing, continuous integration/deployment (CI/CD), and model monitoring
- Collaborate with data science, product, and business partners to translate cutting-edge AI advancements and business opportunities into reliable, production-ready capabilities
- Standardize engineering practices across the team, ensuring high code quality, system performance, and integration with robust security protocols
- Evaluate emerging AI/ML technologies, tools, and methodologies to drive continuous innovation and streamline engineering workflows
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
BASIC QUALIFICATIONS
- 9+ years of software engineering experience
- 5+ years of experience leading, managing, or mentoring technical engineering teams (direct people management or lead architect/delivery lead experience)
- 4+ years of hands-on experience designing, building, and deploying AI/ML solutions, including LLMs, Generative AI, and traditional ML models
- 3+ years of experience with MLOps practices, including ML pipeline orchestration, model monitoring, and automated deployment (CI/CD)
- 3+ years of experience working with major cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes)
- 3+ years of experience with security, access controls, logging, monitoring, performance tuning, disaster recovery, and production operations
PREFERRED QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent experience)
- Experience in healthcare or another highly regulated industry
- Experience implementing Responsible AI frameworks, AI safety protocols, and governance standards
- Proven excellent communication and stakeholder management skills, with the ability to articulate complex technical concepts to non-technical business leaders
- Solid proficiency in programming languages such as Python, PyTorch, TensorFlow, or other modern ML frameworks
All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
COMPENSATION
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $176,700 - $302,900 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.
See All 4,100+ AI ML Engineering Jobs
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Find AI ML Engineering JobsAI ML Engineering Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple324
- Amazon210
- Capital One145
- TikTok99
- Google92
Top Industries Hiring
- Technology & Software1,564
- Electronics & Hardware446
- Consulting & Professional Services297
- Banking & Financial Services293
- Artificial Intelligence231
What Employers Look For
The qualifications that appear most often in AI ML engineering jobs.
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience building, training, and deploying machine learning models in production environments
- Strong understanding of statistics, probability, and core machine learning algorithms
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for model serving
- Experience with data pipelines, feature engineering, and large-scale data processing tools
- Bachelor's or master's degree in computer science, mathematics, statistics, or a related field
Tips for Your AI ML Engineering Job Search
Tailor your resume to each job
AI ML engineering listings vary sharply in stack and method. Match your resume's technical section to the exact frameworks named in the posting, whether that's PyTorch, TensorFlow, JAX, or scikit-learn, so automated screening tools rank you higher before a human ever reads it.
Apply early to roles that fit
Migrate Mate lists ai ml engineering openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Lead with measurable model outcomes
Hiring managers in ai ml engineering care about impact, not methodology alone. Quantify results where you can: latency improvements, accuracy gains, or cost reductions your models produced. A percentage improvement on a production system outweighs a list of libraries you've used.
Build a public project portfolio
Many ai ml engineering roles screen candidates by asking for a GitHub or similar link before a phone screen. Post at least two end-to-end projects, including data preprocessing, training code, evaluation, and a short write-up explaining the tradeoffs you made.
Prepare for the full interview loop
AI ML engineering interviews typically combine coding rounds, ML system design, and a take-home or live modeling exercise. Practice designing scalable serving pipelines and explaining regularization or feature engineering decisions out loud, not just writing code on a whiteboard.
Negotiate with competing offers strategically
AI ML engineering is one of the few fields where counter-offers are expected. If you have multiple final-round processes running simultaneously, let each recruiter know you're actively interviewing elsewhere. Concrete timelines, not vague interest, motivate faster decisions and better offers.
AI ML Engineering Jobs: Frequently Asked Questions
Which companies are hiring the most ai ml engineerings?
The companies hiring the most ai ml engineerings right now include Apple, Amazon, and Capital One, with the largest share of openings in California, New York, and Washington, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in technology, healthcare, and financial services sectors.
How many ai ml engineering jobs are remote?
About 28% of ai ml engineering openings are fully remote or hybrid as of June 2026, making it one of the more remote-friendly engineering disciplines. Research-focused and NLP roles tend to have the highest share of remote flexibility, while roles requiring access to proprietary on-premise data infrastructure are more likely to be on-site.
How do you become a ai ml engineering?
Start by building a strong foundation in Python, linear algebra, calculus, and probability. Work through core machine learning concepts using structured courses or university programs, then implement projects end to end, from raw data to a deployed model. Contribute to open-source repositories or Kaggle competitions to demonstrate applied skills. Pursue a degree or practical bootcamp in computer science, data science, or statistics if you haven't already, and keep current with research papers in your area of focus.
Can I get an ai ml engineering job with little or no experience?
Entry-level ai ml engineering roles do exist, and the path in typically runs through a strong public portfolio rather than years of industry experience. Build two or three end-to-end projects covering different problem types such as classification, regression, or generative modeling, and document your design choices clearly. Internships, research assistant positions, and ML-adjacent roles in data analytics or software engineering are common stepping stones that give you production exposure before moving into a dedicated ML role.
What does the ai ml engineering interview process look like?
Most ai ml engineering interview loops include a recruiter screen, one or two coding rounds focused on data structures and algorithms, an ML fundamentals round covering topics like bias-variance tradeoff and model evaluation, and an ML system design round where you architect a scalable training or serving pipeline. Many companies also include a take-home modeling exercise or a live case study. Final rounds often involve a presentation to the team or a culture-fit conversation with senior engineers or managers.
Where can I find and apply to ai ml engineering jobs?
You can find and apply to ai ml engineering jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the available roles, find the ones that match your skills and seniority level, and apply directly to each listing from the page.
See All 4,100+ AI ML Engineering Jobs
Jump back to the full list of openings and apply to any AI ML engineering role that fits.
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