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Remote Machine Learning Compiler Engineer Jobs in Alameda, CA

Adobe

Staff Machine Learning Engineer

San Jose, CA · On-site +1

As a Staff Machine Learning Engineer (MLE 50), you will design, build, and deploy semantic matching and ranking models that understand text, images, documents, and other content modalities at Adobe ...

Unitytech

Senior Machine Learning Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

We're looking for a Senior Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game ...

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Alameda, CA

Remote Machine Learning Compiler Engineer information

See Alameda, CA salary details

$85K

$189.8K

$232.3K

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

As of Jul 13, 2026, the average yearly pay for remote machine learning compiler engineer in Alameda, CA is $189,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $162,100.00 and $232,300.00 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 Alameda, CA? For Remote Machine Learning Compiler Engineer jobs in Alameda, CA, the most frequently searched job titles are:
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Remote Machine Learning Compiler Engineer jobs near you
Principal Machine Learning Engineer

Principal Machine Learning Engineer

Atlassian

Mountain View, CA • On-site, Remote

Other

Posted 5 days ago

Job description

Overview
As a Principal Machine Learning Engineer, you will drive the development and implementation of cutting-edge machine learning algorithms, training sophisticated models, and collaborating with product, engineering, and analytics teams to build AI functionalities into Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks - designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, ensuring AI's transformative potential is realized across our offerings.
Responsibilities
Technical Leadership & Execution
  • Drive complex decisions that impact the work of teams and change their technical direction over multiple quarters
  • Regularly tackle the largest and most complex problems on the team, from technical design to launch
  • Set the direction of systems and capabilities, balancing progress over perfection
  • Determine plans-of-attack on large projects and solve complex architecture challenges

Model Development & Experimentation
  • Design, develop, and deploy production-grade ML models (e.g., ranking, retrieval, LLM-based systems) to optimize user experience and achieve business objectives
  • Conduct meticulous experimentation and model evaluations, backing decisions with data
  • Develop robust feature engineering practices to ingest, process, and serve features for offline training and online inference at scale
  • Oversee end-to-end deployment of ML solutions into production, ensuring continuous evaluation, monitoring, and improvement

Cross-Functional Collaboration
  • Collaborate closely with product managers, designers, and engineering teams to integrate AI/ML capabilities into products
  • Partner across engineering teams to take on company-wide programs spanning multiple projects
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders

Mentorship & Organizational Impact
  • Mentor and guide junior and senior engineers, fostering a culture of innovation, collaboration, and continuous learning
  • Actively share knowledge and expertise through mentoring and coaching beyond direct reports
  • Contribute to programs of work that scale across the department
  • Identify, solve, and bridge gaps/problems across teams using experience and expertise

Decision Making & Direction
  • Quickly collate and analyze key decision parameters, balancing speed, risk, and impact appropriately
  • Limit ambiguity and risk by experimenting and prototyping
  • Understand how contributions of multiple capabilities fit into larger products and platforms

Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges
In The United States or Remote, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $209,700 - $273,775
Zone B: $188,730 - $246,398
Zone C: $174,051 - $227,233
Qualifications
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.

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