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Remote Machine Learning Compiler Engineer Jobs in San Jose, CA

Staff Machine Learning Engineer

Mountain View, CA ยท On-site +1

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

Lead Machine Learning Engineer (IC)

San Jose, CA ยท On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer (IC) 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.

Sr. Lead Machine Learning Engineer

San Jose, CA ยท 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.

Remote (United States) Employment Type: Direct Hire - Full-Time Compensation: $180K-$250K - based ... Partner closely with engineering, product, and executive leadership to define technical strategy ...

Showing results 41-60

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 Aug 9, 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.

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 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.

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.

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 are popular job titles related to Remote Machine Learning Compiler Engineer jobs in San Jose, CA? For Remote Machine Learning Compiler Engineer jobs in San Jose, CA, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Compiler Engineer jobs in San Jose, CA look for? The top searched job categories for Remote Machine Learning Compiler Engineer jobs in San Jose, CA are:
What cities near San Jose, CA are hiring for Remote Machine Learning Compiler Engineer jobs? Cities near San Jose, CA with the most Remote Machine Learning Compiler Engineer job openings:

Staff Machine Learning Engineer

Omnissa

Mountain View, CA โ€ข On-site, Remote

$162K - $342K/yr

Full-time

Medical, Retirement

Re-posted 21 days ago


Job description

Job Description:

We areOmnissa!
Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-from anywhere experiences. We integrate industry-leading solutions-including Unified Endpoint Management,Virtual Appsand Desktops, Digital Employee Experience, and Security & Compliance-into a seamless, autonomous workspace that adapts to how people work. Our platform boosts employee engagement whileoptimizingIT operations, security, and cost.
Guided by our Core Values-Act in Alignment, Build Trust, Foster Inclusiveness, Drive Efficiency, and Maximize Customer Value-we'regrowing rapidly and committed to delivering meaningful impact. Ifyou'repassionate about shaping the future of work,we'dlove to hear from you.

AtOmnissa, we are committed tomaintaininga fair, consistent, and secure hiring process for all candidates. As part of this approach, we use standard interview and verification practices designed to ensure alignment and protect both candidates and the organization. These practices are applied thoughtfully and with respectforcandidate privacy.

What is the opportunity?

Our platform manages millions of devices across multiple operating systems, requiring exceptional performance, scalability, availability, and resilience. You will join theAI Platform Team, the group responsible for building foundational AI capabilities across theOmnissaproduct ecosystem.

As aStaff Machine Learning Engineer, you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You'llwork closely with engineering and product teams to operationalize models across ourcloudscaleenvironment while driving bestinclass ML engineering practices.You will own engineering initiatives end to end and help foster a culture of high ownership, continuous improvement, and engineering excellence. Here is a breakdown:

Responsibilities

  • Design, develop, and deploy machine learning models for classification, prediction, anomaly detection, and intelligent automation.

  • Build andmaintainscalable data pipelines for model training, evaluation, andrealtime/batch inference.

  • OptimizeML models and pipelines for performance, scalability, reliability, and cost efficiency.

  • Collaborate withcross functionalteams to integrate ML solutions into core platform features and services.

  • Conduct model experimentation, evaluation, and iteration using quantitative metrics and A/B testing as needed.

  • Implement model observability, monitoring, and drift detection to ensure production reliability.

  • Stay current with advancements in machine learning, AI, and LLM technologies, and apply them to product use cases.

What will you bring toOmnissa?

  • 5+ years of experience in machine learning engineering or data science roles.

  • Strongproficiencyin Python and ML frameworks (e.g.,PyTorch, TensorFlow,Scikitlearn).

  • Experience building and operating data processing workflows (batch or streaming) and working with cloud platforms (AWS, Azure, or GCP).

  • Solid understanding of machine learning algorithms, statistics, and model evaluation techniques.

  • Familiarity with containerization and orchestration technologies (Docker, Kubernetes).

  • Handson experience with Large Language Models (LLMs), including finetuning, prompt engineering, and deployment.

  • Knowledge oftext embedding models, and vector databases for Retrieval Augmented Generation (RAG) systems

  • Strongproblem-solvingskills and the ability to collaborate effectively in Agile teams.

  • Highly motivated, adaptable, and eager to learnnew technologies.

Preferred Skills

  • Experience with distributed computing frameworks (e.g., Spark, Ray).

  • Experience with orchestration frameworks (e.g.,LangChain/LangGraph) to build AI agents and multi-agent systems.

  • Experience building feature stores or working with vector databases.

  • Knowledge ofreal-timeinference architectures and model monitoring systems.

  • Experience developing scalable ML services via REST/gRPC.

Location:Mountain View, CA or Atlanta, GA
Location Type:hybrid
Travel Expectations:None
Education:Bachelor's Degree preferred, or equivalent combination of education and relevant professional experience.

Compensation: The typical base salary for this role is betweenUSD $162,512- $342,750per year and it may be eligible for participation in a corporate bonus program. Actual compensation offer may vary from posted hiring range based upon geographic location, work experience, education, skill level, or other relevant factors. In addition to competitive compensation,Omnissaoffers a variety of benefits such as employee ownership, health insurance, 401k with matching contributions, disability insurance,paid-timeoff, growth opportunities, and more.

Omnissais an EqualEmploymentOpportunitycompanyandProhibits Discrimination and Harassment of Any Kind:
Omnissa is committed to the principle of equal employment opportunity and to providing a work environment free of discrimination and harassment. All employment decisions atOmnissaare based on business needs, job requirements and individual qualifications, without regard to race, color, religion, ancestry, ethnicity, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past, present, or prospective service in the uniformed services, family medical history or genetic information, family or parental status, veteran status, or any other status protected by applicable laws or regulations in the locations where we operate.Omnissawill not tolerate discrimination or harassment based on any of these characteristics.Omnissawelcomes applicants of all ages.Omnissawill provide reasonable accommodations to applicants and employees who have protected disabilities consistent with applicable federal,stateand local law.