Applied AI Engineer Jobs
Applied AI Engineer jobs are open across technology, healthcare, finance, and defense, from new-grad to principal and staff level, with specializations in LLM fine-tuning, MLOps, and multimodal systems. Find a role that fits from the openings below and apply directly.
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Showing 5 of 643+ Applied AI Engineer jobs
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
This role may also be located in our Playa Vista, CA campus.
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Mountain View, CA, USA; Los Angeles, CA, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience in management consulting, corporate strategy, go-to-market strategy, sales operations, marketing, finance, or program/project management at a technology or media company.
- Experience with core business operations (e.g., annual business planning, headcount management, running business reviews, or target setting).
- Experience working with executive-level clients or stakeholders.
- Experience in sales operations, planning, and processes (e.g., forecasting, sales compensation, contracting).
- Experience with Go-To-Market (GTM) strategies.
Preferred qualifications:
- Excellent team-work and communication skills to synthesize complex findings into simple, compelling strategic narratives for executive audiences.
- Proven ability to structure complex, multi-variable issues, identify operational inefficiencies, and build innovative processes that prevent future roadblocks.
- Impeccable business judgment to confidently navigate senior-leader pushback, maintain composure, and drive consensus in ambiguous situations.
- Successful track record operating within globally scaled product sales, engineering, or sales technology environments.
- Strong empathy for internal sellers, proposing innovative approaches while clearly outlining risks and trade-offs.
About the job
The Product Operations team sits within the Global Business Applied AI (GBAI) team, and is responsible for leading sales tools strategy across business operations, governance, legal compliance, sales enablement, and measurement and analytics. GBAI resides within the Go to Market Operations (GTM) team and enables Google’s Business Organization (GBO) to drive customer success.
You will be operating under extreme uncertainty, efficiently structuring highly ambiguous, complex problems, and generating clear, actionable insights. You will demonstrate strong decision-making leadership, a bias for action, and the ability to build trusted cross-functional partnerships across global product leads, engineering, product management, legal, compliance, and finance.
The Go-to-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead and drive complex, cross-functional strategic initiatives and processes end-to-end with limited guidance, managing project scoping, planning, priorities, and milestones.
- Deconstruct highly ambiguous situations and solve complex problems that have multiple potential solutions, drawing on a wide toolkit to deliver clear insights and optimal, data-driven recommendations.
- Build and influence a broad network of relationships across the product area, including Director-level stakeholders, to align resources, build consensus on complex issues, and drive change management.
- Design reporting frameworks and analyze operational data to surface actionable insights, track progress against business objectives, and empower executive decision-making.
- Serve as a subject matter expert with a thorough understanding of the business area. Develop others by sharing expertise, teaching deep systems/product knowledge, and providing support/direction across adjacent workstreams.
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
This role may also be located in our Playa Vista, CA campus.
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Mountain View, CA, USA; Los Angeles, CA, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience in management consulting, corporate strategy, go-to-market strategy, sales operations, marketing, finance, or program/project management at a technology or media company.
- Experience with core business operations (e.g., annual business planning, headcount management, running business reviews, or target setting).
- Experience working with executive-level clients or stakeholders.
- Experience in sales operations, planning, and processes (e.g., forecasting, sales compensation, contracting).
- Experience with Go-To-Market (GTM) strategies.
Preferred qualifications:
- Excellent team-work and communication skills to synthesize complex findings into simple, compelling strategic narratives for executive audiences.
- Proven ability to structure complex, multi-variable issues, identify operational inefficiencies, and build innovative processes that prevent future roadblocks.
- Impeccable business judgment to confidently navigate senior-leader pushback, maintain composure, and drive consensus in ambiguous situations.
- Successful track record operating within globally scaled product sales, engineering, or sales technology environments.
- Strong empathy for internal sellers, proposing innovative approaches while clearly outlining risks and trade-offs.
About the job
The Product Operations team sits within the Global Business Applied AI (GBAI) team, and is responsible for leading sales tools strategy across business operations, governance, legal compliance, sales enablement, and measurement and analytics. GBAI resides within the Go to Market Operations (GTM) team and enables Google’s Business Organization (GBO) to drive customer success.
You will be operating under extreme uncertainty, efficiently structuring highly ambiguous, complex problems, and generating clear, actionable insights. You will demonstrate strong decision-making leadership, a bias for action, and the ability to build trusted cross-functional partnerships across global product leads, engineering, product management, legal, compliance, and finance.
The Go-to-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead and drive complex, cross-functional strategic initiatives and processes end-to-end with limited guidance, managing project scoping, planning, priorities, and milestones.
- Deconstruct highly ambiguous situations and solve complex problems that have multiple potential solutions, drawing on a wide toolkit to deliver clear insights and optimal, data-driven recommendations.
- Build and influence a broad network of relationships across the product area, including Director-level stakeholders, to align resources, build consensus on complex issues, and drive change management.
- Design reporting frameworks and analyze operational data to surface actionable insights, track progress against business objectives, and empower executive decision-making.
- Serve as a subject matter expert with a thorough understanding of the business area. Develop others by sharing expertise, teaching deep systems/product knowledge, and providing support/direction across adjacent workstreams.
Applied AI Engineer Jobs by Experience Level
Top Cities Hiring Applied AI Engineers
Explore applied AI engineer openings in the cities hiring most right now.
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Find Applied AI Engineer JobsApplied AI Engineer Job Market
Who's Hiring
- Amazon39
- Amazon Web Services37
- Anthropic30
- JPMorganChase30
- OpenAI22
Top Industries Hiring
- Technology & Software41
- Science & Research17
- Banking & Financial Services8
- Fintech7
- Distribution & Wholesale5
What Employers Look For
The qualifications that appear most often in applied AI engineer jobs.
- Proficiency in Python with hands-on experience building and deploying machine learning models
- Experience with large language models and frameworks such as PyTorch, Hugging Face, or LangChain
- Familiarity with MLOps tooling including model versioning, monitoring, and CI/CD pipelines
- Bachelor's or master's degree in computer science, machine learning, or a closely related field
- Experience integrating AI models into production software systems via APIs or microservices
- Working knowledge of cloud platforms such as AWS, Google Cloud, or Azure for model serving
Tips for Your Applied AI Engineer Job Search
Tailor your resume to production depth
Hiring managers distinguish candidates who have deployed models in production from those who have only run experiments. Call out inference latency improvements, cost reductions, or uptime metrics from systems you owned end to end, not just notebooks you built.
Show your model evaluation methodology
Interviewers for applied AI roles probe how you measure whether a model actually works in the real world. Document your evals framework, the failure modes you caught before launch, and how you iterated, so you can speak to this concisely and specifically.
Target roles by tech stack, not just title
Applied AI engineer openings vary widely by stack. Filter by the tools you know best, whether that's LangChain, vLLM, or PyTorch with CUDA, so you apply where your day-one contribution is clearest to the hiring team reading your resume.
Apply early to roles that fit
Migrate Mate lists applied ai engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prep a system design answer for AI pipelines
Most applied AI interviews include a system design round specific to ML infrastructure. Practice walking through prompt chaining, retrieval-augmented generation retrieval flow, or batch inference architecture out loud, focusing on trade-offs rather than a single correct answer.
Negotiate on compute access, not just compensation
Applied AI engineers often find that GPU budgets and model API access affect their day-to-day more than title. Before accepting an offer, ask directly what compute resources the team uses and how new projects get resourced, so you can assess the role accurately.
Applied AI Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most applied ai engineers?
The companies hiring the most applied ai engineers right now include Amazon, Amazon Web Services, and Anthropic, with the largest share of openings in California, New York, and Washington, based on current listings on Migrate Mate as of November 2026. Demand is concentrated at companies actively building or integrating AI-powered products rather than conducting pure research.
How many applied ai engineer jobs are remote?
About 78% of applied ai engineer openings are fully remote or hybrid as of November 2026, making this one of the more flexible engineering roles in the market. Sub-areas with the highest remote share include prompt engineering, LLM integration, and retrieval-augmented generation work, where collaboration with on-site hardware is rarely required.
How do you become an applied ai engineer?
Build a strong foundation in Python and machine learning fundamentals, then move into hands-on projects that take a model from training through deployment. Focus on production experience, including API integration, monitoring, and evaluation frameworks. Contributing to open-source AI tooling and publishing documented project work signals to employers that you can ship, not just prototype.
Can you get hired as an applied ai engineer with little experience?
Yes, entry-level applied AI roles exist, but employers expect demonstrable project work even without professional experience. Build public repositories showing end-to-end pipelines, fine-tuned models, or RAG implementations with documented evals. Roles at startups building AI-native products and companies expanding AI teams often have more flexibility on years of experience than established enterprises do.
What does the applied ai engineer interview process look like?
Most processes include a recruiter screen, a technical phone interview covering Python and ML fundamentals, a take-home or live coding exercise focused on building or evaluating a model pipeline, and a system design round specific to AI architecture. Final rounds often include a presentation of past project work and a conversation about how you measure model quality in production.
Where can I find and apply to applied ai engineer jobs?
You can find and apply to applied ai engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your skills and experience level, then apply directly to each one that fits.
See All 643+ Applied AI Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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