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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Location: New York
Other locations: Anywhere in Country
Salary: Competitive
Date: Jul 21, 2026
Job description
Requisition ID: 1719191
Location: Anywhere in Country
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The opportunity
Our Artificial Intelligence and Data team helps apply cutting-edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.
In this role, you will research, build, and implement scalable artificial intelligence systems that learn and make predictions tailored to business requirements across various environments, including cloud and on premises. You will enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions.
Within Power & Utilities engagements, these solutions will commonly support regulated environments such as electric, gas, and water utilities, addressing domains including grid and asset reliability, outage prediction and response, capital planning, customer operations, regulatory reporting, and operational efficiency across generation, transmission, distribution, and field operations.
Your key responsibilities
As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities—such as safety, reliability, affordability, and compliance—into scalable AI-enabled solutions.
Your responsibilities will include:
- Leading workstream delivery and ensuring the effective management of processes and projects.
- Continuously improving processes by identifying innovative solutions through research and analysis.
- Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
- Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
- Identifying opportunities for additional services and managing engagement economics.
- Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
- Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
- Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services.
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
- Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
- Strong judgment in selecting methods and techniques for obtaining results.
- Experience in managing client relationships and delivering high-quality service.
- Ability to lead teams effectively and manage change within the organization.
- Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
- Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.
To qualify for the role, you must have
- A Bachelor’s degree required (4-year degree).
- 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning.
- 2-4 years of experience directly managing technical teams.
- Strong skills in Python.
- Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams.
- Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform.
- Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch.
- Experience with natural language processing and deep learning.
- Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions.
- Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation.
- Experience with model retraining and feedback loop methodologies.
- Experience with model and solution monitoring and reporting.
- Understanding of data structures, data modelling and software engineering best practices.
- Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques.
- Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements.
- Skills in Technical Design Optimization.
- Strong relationship-building skills.
- Demonstrated client trust and value.
- Digital fluency and emotional agility.
- Commercial acumen and negotiation skills.
- Proven ability to lead teams and manage change.
- Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
- Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
Ideally, you’ll also have
- A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
- Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field.
- Experience working with diverse teams to deliver complex solutions.
- Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
- Experience fine-tuning Generative AI models.
- Experience in managing complex projects with multiple stakeholders.
- A strong understanding of industry trends and emerging technologies.
- Skills in data visualization and storytelling with data.
- Experience with image processing techniques and/or speech and audio processing and analysis.
- Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
- Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
What we look for
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.
What we offer you
At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.
- We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $125,500 to $230,200. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $150,700 to $261,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
- Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
- Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
Are you ready to shape your future with confidence? Apply today.
EY accepts applications for this position on an ongoing basis.
For those living in California, please click here for additional information.
EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at ssc.customersupport@ey.com.
AI ML Engineering Jobs by Experience Level
Top Cities Hiring AI ML Engineerings
Explore AI ML engineering openings in the cities hiring most right now.
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Find AI ML Engineering JobsAI ML Engineering Job Market
Who's Hiring
- JPMorganChase17

- Amazon Web Services10

- Booz Allen Hamilton6

- EY5

- AMD5

Top Industries Hiring
- Banking & Financial Services10
- Technology & Software9
- Investment & Asset Management5
- Automotive4
- Electronics & Hardware4
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 JPMorganChase, Amazon Web Services, and Booz Allen Hamilton, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in technology, healthcare, and financial services sectors.
How many ai ml engineering jobs are remote?
About 73% of ai ml engineering openings are fully remote or hybrid as of November 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 143+ AI ML Engineering Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI ML Engineering Jobs