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Remote Machine Learning Compiler Engineer Jobs in San Jose, CA

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

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Remote Machine Learning Compiler Engineer information

See San Jose, CA salary details

$87.9K

$196.2K

$240.3K

How much do remote machine learning compiler engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote machine learning compiler engineer in San Jose, CA is $196,235.00, according to ZipRecruiter salary data. Most workers in this role earn between $167,600.00 and $240,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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Remote Machine Learning Compiler Engineer jobs near you

Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home

Ginas Tech Jobs

San Francisco, CA • Remote

Full-time

Medical, Dental, Vision, PTO

Re-posted 28 days ago

Job description

Job Description

Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home

As the Staff Machine Learning Engineer, you own the execution layer of intelligence.  You translate research direction into reliable, scalable, production-grade Machine Learning (ML) systems.  This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints.  This position is 100% Remote.

Staff Machine Learning Engineer Responsibilities:

- Own end-to-end Machine Learning (ML) system execution:  data pipelines, training workflows, evaluation systems, inference architecture, and deployment.

- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.

- Architect and operate scalable inference systems, balancing latency, cost, and reliability.

- Design and maintain data systems for high-quality synthetic and real-world training data.

- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.

- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.

- Collaborate closely with application engineering to integrate Machine Learning (ML) systems cleanly into backend, mobile, and desktop products.

- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.

- Work under real production constraints: latency, cost, reliability, and safety

Staff Machine Learning Engineer Outcomes

- Research and models reliably translate into production-ready solutions with clear performance and quality targets.

- Machine Learning (ML) pipelines, training loops, and inference systems are stable, efficient, and maintainable.

- Production issues are detected, debugged, and resolved quickly, minimizing user impact.

- Team members are supported, aligned, and able to deliver high-impact Machine Learning (ML) work with minimal friction.

- Iterations on models and systems are measurable, safe, and improve user experience over time.

Qualifications

Staff Machine Learning Engineer Qualifications:

- Experience building or shipping real Machine Learning (ML) systems used by people, not just demos.

- Artificial Intelligence (AI) experience required.

- Experience working with large models and understanding their failure modes.

- Experience writing strong, production-grade code.

- You are self-directed, pragmatic, and take full ownership of outcomes.

- Experience communicating clearly and collaborate well in small, high-trust teams.

- Tech Stack:  GPU-based training and inference system, JAX, Python, and PyTorch.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

Keywords:  San Francisco CA Jobs, Staff Machine Learning Engineer, Data Pipelines, DPO, GPU, JAX, LoRA, Machine Learning Engineer, ML, Machine Learning, Python, PyTorch, QLoRA, SFT, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting

Looking to hire a Staff Machine Learning Engineer in San Francisco, CA or in other cities?  Our IT recruiting agencies and staffing companies can help.

We help companies that are looking to hire Staff Machine Learning Engineers for jobs in San Francisco, California and in other cities too.  Please contact our IT recruiting agencies and IT staffing companies today!

Additional Information

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