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Junior Machine Learning Compiler Engineer Jobs in San Ramon, CA

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$500 - $5.0K/wk

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML ... We run a structured onboarding programme for junior hires including a dedicated mentor, a 90-day ...

femtoAI

ML Compiler Engineer

San Bruno, CA · On-site

You will work on a custom ML compiler that transforms modern ML and DSP models into highly ... Understanding of deep learning models (conv, sequence models, etc.) * Ability to reason about ...

femtoAI

ML Compiler Engineer

San Bruno, CA · On-site

You will work on a custom ML compiler that transforms modern ML and DSP models into highly ... Understanding of deep learning models (conv, sequence models, etc.) * Ability to reason about ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110K - $165K/yr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

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All JobsMachine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer Jobs in San Ramon, CA

Junior Machine Learning Compiler Engineer information

See San Ramon, CA salary details

$37.4K

$80.2K

$122.4K

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

As of Sep 9, 2026, the average yearly pay for junior machine learning compiler engineer in San Ramon, CA is $80,237.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,200.00 and $89,400.00 per year, depending on experience, location, and employer.

What does a junior machine learning compiler engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are typical projects and responsibilities for a junior machine learning compiler engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

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

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

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

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

What are popular job titles related to Junior Machine Learning Compiler Engineer jobs in San Ramon, CA?

For Junior Machine Learning Compiler Engineer jobs in San Ramon, CA, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning Compiler Engineer jobs in San Ramon, CA look for?

The top searched job categories for Junior Machine Learning Compiler Engineer jobs in San Ramon, CA are:

What cities near San Ramon, CA are hiring for Junior Machine Learning Compiler Engineer jobs?

Cities near San Ramon, CA with the most Junior Machine Learning Compiler Engineer job openings:

Junior Machine Learning Compiler Engineer jobs near you
Infographic showing various Junior Machine Learning Compiler Engineer job openings in San Ramon, CA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $80,237 per year, or $38.6 per hour.

Senior Principal Machine Learning Engineer

San Jose, CA • On-site

SambaNova
See more jobs at SambaNovaexternal

$220K - $300K/yr

Full-time

Medical, Dental, Vision, Life

Posted 23 days ago

Job description

The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale.
SambaNova Suiteâ„¢ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets.
About the team
The ML team builds and optimizes the models that run on SambaNova's RDU accelerators. Their work covers model architecture, training and fine-tuning, inference optimization, evaluation, and data curation, and it lands in SambaStack and SambaCloud. They work directly with the compiler, systems, and hardware teams on co-design, so decisions about a model shape decisions about the silicon it runs on.
About the role
As a Senior Principal Machine Learning Engineer, you will be responsible for designing, developing, and optimizing machine learning models-with a focus on cutting-edge Large Language Models (LLMs)-to run efficiently on SambaNova's specialized hardware architecture, including the RDU. This critical role bridges advanced LLM research and practical deployment, involving the development of model architectures, improving training and inference efficiency, and collaborating on hardware-software co-design with compiler, systems, and hardware teams. The engineer will also act as the ML expert, guiding the integration of LLM solutions into production systems and customer-facing products like SambaStack and SambaCloud, with work spanning the full lifecycle from training and inference to evaluation and data curation.
Responsibilities
Some of your responsibilities will include:
  • Define and drive technical strategy for ML model development, training pipelines, and inference systems on SambaNova's RDU and broader hardware ecosystem
  • Lead hardware-software co-design efforts in close collaboration with compiler, systems, and hardware teams-shaping architectural decisions that unlock performance at scale
  • Identify, evaluate, and champion state-of-the-art ML techniques (e.g., speculative decoding, reinforcement learning, mixture-of-experts, long-context modeling) for adoption and adaptation on reconfigurable dataflow architectures
  • Serve as the senior technical voice in critical design reviews, architectural decisions, and cross-functional planning-providing guidance that influences product and engineering roadmaps
  • Mentor and develop principal and senior ML engineers, elevating the technical capabilities of the organization through active collaboration, design feedback, and knowledge transfer
  • Partner with product and engineering leadership to translate complex ML capabilities into scalable, customer-facing solutions in SambaStack and SambaCloud
  • Drive resolution of the most complex, ambiguous technical challenges-including those that span organizational boundaries or require novel approaches not yet established in the field
Required Qualifications
  • B.S. in Computer Science, Electrical Engineering, or related field
  • 8+ years of industry experience in machine learning engineering, with a demonstrated record of technical leadership on large-scale or novel ML systems
  • Deep expertise in LLM training, fine-tuning, inference optimization, and evaluation at scale
  • Strong background in ML algorithms, deep learning architectures, and modern training methodologies, with the ability to critically evaluate and advance the state of the art
  • Demonstrated ability to lead and align cross-functional technical efforts, mentor senior engineers, and influence organizational direction without direct management authority
  • Track record of independently scoping and delivering high-complexity, high-ambiguity technical projects

Preferred Qualifications
  • M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field
  • Experience with hardware-software co-design with non-GPU accelerators
  • Publications or open-source contributions in LLM training or inference
  • Experience with speculative decoding, mixture-of-experts, or long-context modeling in production
  • Experience with reinforcement learning for post-training
  • Familiarity with compiler or kernel-level optimization for ML workloads

Base Salary Range:
Base Pay Range
$220,000-$300,000 USD
Submission GuidelinesPlease note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified.
EEO PolicySambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Benefits Summary for US-Based, Full-Time Employment Positions
SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

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