AI ML Engineer Jobs
AI ML Engineer jobs are open across technology, healthcare, financial services, and defense, from entry-level to staff and principal, with specializations in deep learning, natural language processing, and computer vision. Find a role that fits from the openings below and apply directly.
Find AI ML Engineer JobsLooking for remote work? View remote AI ML engineer jobs →Student or new grad? View AI ML engineer internships →Overview
Showing 5 of 295+ AI ML Engineer jobs
Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Senior Machine Learning Engineer to help shape the future of responsible AI evaluation for the next generation of generative features.
In this role, you will work to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. Your work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll anticipate safety risks and deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Senior Machine Learning Engineer to drive Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical execution for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and implementing robust data pipelines to produce reliable, scalable insights that inform ship/no-ship product decisions.
Pre- and post-launch, you will be deeply hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a senior technical leader on the team, you will champion technical excellence, empower leadership with data-driven safety recommendations, and systematically solve complex engineering roadblocks. This role heavily draws on applied data science, scientific investigation, cross-functional collaboration, and defending safety metrics to stakeholders and decision-makers.
Preferred Qualifications
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
Develop metrics for the evaluation of safety and fairness risks inherent to generative models and Gen-AI features.
Design datasets, identify data needs, and implement creative solutions to scale and expand data coverage through human and synthetic generation methods.
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale.
Design, implement, and optimize data pipelines, collaborating cross-functionally to execute end-to-end safety evaluations.
Drive operational excellence by automating manual workflows and optimizing evaluation velocity to meet rapid product release cycles.
Distill complex project findings into actionable insights for product engineering teams and safety policy development.
Work with highly-sensitive content, including exposure to offensive and controversial material.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $165,800 and $292,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Senior Machine Learning Engineer to help shape the future of responsible AI evaluation for the next generation of generative features.
In this role, you will work to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. Your work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll anticipate safety risks and deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Senior Machine Learning Engineer to drive Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical execution for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and implementing robust data pipelines to produce reliable, scalable insights that inform ship/no-ship product decisions.
Pre- and post-launch, you will be deeply hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a senior technical leader on the team, you will champion technical excellence, empower leadership with data-driven safety recommendations, and systematically solve complex engineering roadblocks. This role heavily draws on applied data science, scientific investigation, cross-functional collaboration, and defending safety metrics to stakeholders and decision-makers.
Preferred Qualifications
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
Develop metrics for the evaluation of safety and fairness risks inherent to generative models and Gen-AI features.
Design datasets, identify data needs, and implement creative solutions to scale and expand data coverage through human and synthetic generation methods.
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale.
Design, implement, and optimize data pipelines, collaborating cross-functionally to execute end-to-end safety evaluations.
Drive operational excellence by automating manual workflows and optimizing evaluation velocity to meet rapid product release cycles.
Distill complex project findings into actionable insights for product engineering teams and safety policy development.
Work with highly-sensitive content, including exposure to offensive and controversial material.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $165,800 and $292,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
AI ML Engineer Jobs by Experience Level
Top Cities Hiring AI ML Engineers
Explore AI ML engineer openings in the cities hiring most right now.
See All 295+ AI ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI ML Engineer JobsAI ML Engineer Job Market
Who's Hiring
- Atlas Technologies22
- JPMorganChase21
- Amazon Web Services13
- GEICO9
- TikTok9
Top Industries Hiring
- Technology & Software16
- Insurance10
- Banking & Financial Services10
- Investment & Asset Management6
- Electronics & Hardware5
What Employers Look For
The qualifications that appear most often in AI ML engineer jobs.
- Proficiency in Python and at least one ML framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Strong foundation in statistics, linear algebra, and probability theory
- Familiarity with MLOps tools and platforms including Kubeflow, MLflow, or SageMaker
- Experience working with large datasets using SQL, Spark, or distributed computing frameworks
- Bachelor's or master's degree in computer science, mathematics, or a related quantitative field
Tips for Your AI ML Engineer Job Search
Tailor your resume to each stack
Recruiters scan for specific frameworks like PyTorch, TensorFlow, or JAX before reading anything else. Match the exact tool names listed in the job description, and call out model types you've trained or fine-tuned rather than listing ML as a general skill.
Show inference costs, not just accuracy
Most job descriptions ask for production ML experience. Quantify latency improvements, model compression ratios, or infrastructure cost reductions you've driven. Accuracy metrics alone don't signal you've shipped a model that runs reliably at scale.
Target openings by model domain, not job title
Titles vary wildly across companies. Search for the domain you work in, like recommendation systems, time-series forecasting, or LLM fine-tuning, in addition to the job title. You'll surface relevant roles that use different naming conventions.
Apply early to roles that fit
Migrate Mate lists ai ml engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design answer for ML pipelines
Most ai ml engineer interviews include a round where you design a full ML system end to end. Practice walking through data ingestion, feature engineering, training infrastructure, model serving, and monitoring before you get on the call.
Negotiate on compute budget, not just compensation
When you reach the offer stage, ask about GPU or TPU access, cloud credits, and whether the team uses managed services or builds infrastructure internally. These details affect your day-to-day work and your ability to ship, and they're fully negotiable.
AI ML Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ai ml engineers?
The companies hiring the most ai ml engineers right now include Atlas Technologies, JPMorganChase, and Amazon Web Services, with the largest share of openings in California, Texas, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in companies building large-scale recommendation systems, generative AI products, and enterprise ML platforms.
How many ai ml engineer jobs are remote?
About 78% of ai ml engineer openings are fully remote or hybrid as of November 2026, making it one of the more flexible engineering roles available. Research and applied science positions tend to offer the most remote flexibility, while roles tied to real-time inference infrastructure or on-premise hardware more often require on-site presence.
How do you become an ai ml engineer?
Build a foundation in Python, linear algebra, and statistics, then work through core ML concepts using publicly available courses and datasets. Develop hands-on projects that go beyond training a model, covering feature pipelines, evaluation, and deployment. Contribute to open-source ML projects or Kaggle competitions to build a visible portfolio, then apply to roles that match your domain focus.
Can you get an ai ml engineer job with little or no experience?
Yes, but you need a portfolio that demonstrates you can move a model from experiment to production. Build end-to-end projects that include data preprocessing, model selection, evaluation, and a deployed endpoint. Entry-level roles and ML engineering apprenticeships at product companies are the most accessible starting points for candidates without formal industry experience.
What does the ai ml engineer interview process look like?
Most ai ml engineer interview processes include a recruiter screen, a take-home or live coding round focused on Python and data manipulation, an ML system design round where you architect a full pipeline, and a behavioral round. Senior roles often add a research presentation or a deep-dive into a past project you've shipped, with questions on trade-offs and production challenges.
Where can I find and apply to ai ml engineer jobs?
You can find and apply to ai ml engineer jobs on Migrate Mate, which lists current openings from companies across the United States. Search for roles that match your specialization and experience level, then apply directly to each listing that fits.
See All 295+ AI ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI ML Engineer Jobs