Software Engineer AI Jobs
Software Engineer AI jobs are open across tech, finance, healthcare, and defense, from new-grad to principal and staff levels, with specializations in machine learning infrastructure, generative AI systems, and model evaluation. Find a role that fits from the openings below and apply directly.
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In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Seattle, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with image processing, computer vision, or machine learning applications.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of this team, you will focus on productionizing GenAI shopping features across Google’s most prominent surfaces, including Search, Commerce, Ads, Chrome, and YouTube. Here, you will master the art of scaling multimodal GenAI to production-level quality, leveraging Google’s infrastructure to deliver highly customized, industry-defining user experiences.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Seattle, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with image processing, computer vision, or machine learning applications.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of this team, you will focus on productionizing GenAI shopping features across Google’s most prominent surfaces, including Search, Commerce, Ads, Chrome, and YouTube. Here, you will master the art of scaling multimodal GenAI to production-level quality, leveraging Google’s infrastructure to deliver highly customized, industry-defining user experiences.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
Software Engineer AI Jobs by Experience Level
Top Cities Hiring Software Engineer AIs
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Find Software Engineer AI JobsSoftware Engineer AI Job Market
Who's Hiring
- JPMorganChase83
- Google65
- Amazon38
- TikTok22
- Meta20
Top Industries Hiring
- Technology & Software24
- Banking & Financial Services8
- Education3
- Energy1
- Insurance1
What Employers Look For
The qualifications that appear most often in software engineer AI jobs.
- Bachelor's or master's degree in computer science, machine learning, or a related field
- Proficiency in Python and hands-on experience with PyTorch or TensorFlow
- Experience building, fine-tuning, or deploying large language models or foundation models
- Familiarity with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML
- Understanding of MLOps practices including model versioning, monitoring, and CI/CD for ML pipelines
- Experience with data pipelines, feature engineering, and working with large-scale datasets
Tips for Your Software Engineer AI Job Search
Tailor your resume to model types
List the specific model architectures you've worked with, such as transformer-based models, diffusion models, or reinforcement learning systems. Recruiters screening software engineer ai resumes look for these terms before they read anything else on the page.
Show evaluation and safety work
Many software engineer ai roles now require experience with benchmarking, red-teaming, or RLHF pipelines. If you've run evals or built safety guardrails, put those projects front and center rather than burying them under general ML work.
Filter openings by inference versus training focus
Software engineer ai roles split sharply between training infrastructure and inference optimization. Know which side you're strongest on and filter for it. Applying to both without adjusting your application often reads as unfocused to hiring teams.
Apply early to roles that fit
Migrate Mate lists software engineer ai openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a systems design answer for AI scale
Software engineer ai interviews almost always include a systems design round focused on serving models at scale, handling latency constraints, or managing GPU resource allocation. Prep these scenarios specifically, not generic distributed systems answers.
Negotiate with deployment artifacts in mind
When you reach the offer stage, ask about compute access, model access tiers, and publication rights alongside salary. These terms matter as much as base pay for a software engineer ai role and are often negotiable earlier than candidates realize.
Software Engineer AI Jobs: Frequently Asked Questions
Which companies are hiring the most software engineer ais?
The companies hiring the most software engineer ais right now include JPMorganChase, Google, and Amazon, with the largest share of openings in California, Washington, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is concentrated at companies building or integrating generative AI products across both consumer and enterprise markets.
How many software engineer ai jobs are remote?
About 80% of software engineer ai openings are fully remote or hybrid as of November 2026, making it one of the more remote-accessible engineering disciplines. Roles focused on model evaluation, prompt engineering infrastructure, and AI safety research tend to have the highest share of fully remote positions compared to hardware-adjacent or inference optimization roles.
How do you become a software engineer ai?
Start by building a solid foundation in Python, linear algebra, and statistics, then move into machine learning fundamentals through coursework or self-study. Work through hands-on projects involving model training, fine-tuning, and evaluation using open-source frameworks. Contribute to public AI projects or publish reproducible experiments to demonstrate applied skill. Then target roles that match your current depth, whether that's ML infrastructure, model development, or AI product engineering.
Can you get hired as a software engineer ai with little experience?
Yes, entry-level and associate software engineer ai roles exist, but they require demonstrated hands-on project work rather than credentials alone. Build and document at least two end-to-end projects, such as a fine-tuned open-source model or a retrieval-augmented generation system, and publish them publicly. Apply to companies known for structured onboarding in AI teams, and target roles that mention mentorship or research engineering rotations.
What does the software engineer ai interview process look like?
The software engineer ai interview process typically includes a recruiter screen, a technical phone interview covering ML concepts and coding, a take-home or live coding exercise involving model implementation or debugging, and a systems design round focused on AI infrastructure or serving at scale. Final rounds often include a cross-functional interview with product or research stakeholders and may include a presentation of prior project work.
Where can I find and apply to software engineer ai jobs?
You can find and apply to software engineer ai jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits. No intermediary steps are needed between finding a role and submitting your application.
See All 1,359+ Software Engineer AI Jobs
Find roles that match your experience and apply in just a few clicks.
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