ML Software Engineer Jobs in Mountain View, CA
ML Software Engineer jobs in Mountain View are concentrated in the North Bayshore tech corridor, Shoreline West, and the Castro Street office cluster, with heavy demand from enterprise AI platforms, autonomous systems, and cloud infrastructure companies, including Nuro, Google, and Waymo. Specialties in large language models, MLOps, and computer vision see the most active recruiting. Scan the live roles below and apply to whichever ones fit.
Find ML Software Engineer JobsOverview
Showing 5 of 114+ ML Software Engineer jobs
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience programming in C++ or Python.
- 2 years of experience with software design and architecture.
- 2 years of experience testing, and launching software products.
- Experience with ML model optimization.
- Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience with debugging correctness and performance issues at all levels of the ML software stack.
- Experience with ML compilers and their internals, experience writing compiler optimization passes.
- Familiarity with accelerator hardware architectures (TPUs/GPUs).
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
On this team, you will own the optimization of the models powering the YouTube algorithm. Your work will focus on model efficiency optimization, such as low-precision quantization , knowledge distillation, parameter sharing, and designing hardware-friendly model architectures, to reduce training and serving costs while maximizing fleet utilization and value delivered to users.
You will build support and optimize new and existing models in our Recommendation System stack, including new model architectures while adapting to next-generation TPU hardware.
You will engage in model and TPU compiler co-design, with opportunities to work across the stack ranging from end-user ML models down to Hardware/Software architecture.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.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
- Profile ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
- Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
- Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
- Partner closely with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience programming in C++ or Python.
- 2 years of experience with software design and architecture.
- 2 years of experience testing, and launching software products.
- Experience with ML model optimization.
- Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience with debugging correctness and performance issues at all levels of the ML software stack.
- Experience with ML compilers and their internals, experience writing compiler optimization passes.
- Familiarity with accelerator hardware architectures (TPUs/GPUs).
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
On this team, you will own the optimization of the models powering the YouTube algorithm. Your work will focus on model efficiency optimization, such as low-precision quantization , knowledge distillation, parameter sharing, and designing hardware-friendly model architectures, to reduce training and serving costs while maximizing fleet utilization and value delivered to users.
You will build support and optimize new and existing models in our Recommendation System stack, including new model architectures while adapting to next-generation TPU hardware.
You will engage in model and TPU compiler co-design, with opportunities to work across the stack ranging from end-user ML models down to Hardware/Software architecture.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.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
- Profile ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
- Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
- Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
- Partner closely with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.
See All 114+ ML Software Engineer Jobs in Mountain View
Find roles in Mountain View that match your experience and apply in just a few clicks.
Find ML Software Engineer JobsML Software Engineer Job Market in Mountain View
Who's Hiring
- Nuro38
- Google32
- Waymo6
- Youtube6
- LinkedIn6
Top Industries Hiring
- Technology & Software51
- Automotive6
- Electronics & Hardware6
- Banking & Financial Services6
ML Software Engineer Jobs in Mountain View: Frequently Asked Questions
How do I get a ml software engineer job in Mountain View?
Focus on the AI product and infrastructure companies concentrated in North Bayshore and the Shoreline West corridor, where demand for ml software engineers runs deepest. Hands-on experience with production ML systems, distributed training, or model deployment pipelines gives you a real edge here. The local market rewards candidates who can point to shipped models, not just academic projects, so a strong GitHub portfolio or documented inference optimization work stands out.
Which companies hire ml software engineers in Mountain View?
Companies currently hiring ml software engineers in Mountain View include Nuro, Google, and Waymo, per current listings on Migrate Mate as of September 2026. Mountain View's employer mix skews heavily toward established tech giants and well-funded AI startups, many headquartered or with major engineering offices right in the city.
Are there remote ml software engineer jobs in Mountain View?
Yes, though roles tied to on-site compute clusters, robotics, or hardware-adjacent ML work tend to require in-person presence. About 20% of ml software engineer openings tied to Mountain View are remote or hybrid as of September 2026, with the remote share concentrated in modeling, data pipeline, and applied research roles where collaboration happens asynchronously.
How can I get a ml software engineer job in Mountain View with little or no experience?
The most realistic entry path in Mountain View is through ML infrastructure or data engineering roles at mid-size AI companies along the North Bayshore corridor, where teams are lean enough to give early-career engineers production exposure quickly. Targeting associate ML engineer or ML platform engineer titles at Series B and C startups improves your odds compared to competing for senior-heavy headcount at large tech campuses. Contributing to open-source ML frameworks and completing a documented end-to-end deployment project makes a meaningful difference in local recruiting screens.
Which industries hire the most ml software engineers in Mountain View?
Mountain View ml software engineer roles concentrate in Technology & Software, Automotive, and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. Mountain View's density of AI-first product companies and major cloud platform offices means those sectors consistently drive the largest share of local openings year-round.
Related Jobs in California
See All 114+ ML Software Engineer Jobs in Mountain View
Find roles in Mountain View that match your experience and apply in just a few clicks.
Find ML Software Engineer Jobs