Machine Learning Engineer
Menlo Park, CA · On-site
The Machine Learning Engineer will architect and develop high-performance AI systems, manage large ... growth startup environment Company : AI models for electronics Founded in , the company is ...
Machine Learning Engineer
Menlo Park, CA · On-site
The Machine Learning Engineer will architect and develop high-performance AI systems, manage large ... growth startup environment Company : AI models for electronics Founded in , the company is ...
Responsibilities : • Develop, optimize, and deploy lightweight machine learning models for edge ... paced startup environment. • Ability to provide mentorship, technical guidance, and career ...
Responsibilities : • Develop, optimize, and deploy lightweight machine learning models for edge ... paced startup environment. • Ability to provide mentorship, technical guidance, and career ...
As a Machine Learning Engineer, you'll be integral in developing state-of-the-art AI intelligence ... Atoms is a robotics startup that develops industrial robotics and physical AI systems to automate ...
As a Machine Learning Engineer, you'll be integral in developing state-of-the-art AI intelligence ... Atoms is a robotics startup that develops industrial robotics and physical AI systems to automate ...
Job Summary : TriFetch is a company focused on AI and machine learning solutions, and they are ... TriFetch is a San Francisco-based healthcare AI startup focused on bridging AI foundations with ...
Job Summary : TriFetch is a company focused on AI and machine learning solutions, and they are ... TriFetch is a San Francisco-based healthcare AI startup focused on bridging AI foundations with ...
... Machine Learning Scientist with deep expertise in building and deploying production machine ... You thrive in a fast-paced startup environment and are motivated by building models that don't just ...
... Machine Learning Scientist with deep expertise in building and deploying production machine ... You thrive in a fast-paced startup environment and are motivated by building models that don't just ...
Machine Learning Engineer
Sunnyvale, CA · On-site
$150K - $277K/yr
Sunnyvale, California, United States -- Machine Learning and AI Our team delivers algorithms that ... This role might also be eligible for discretionary bonuses or commission payments as well as ...
Machine Learning Engineer
Sunnyvale, CA · On-site
$150K - $277K/yr
Sunnyvale, California, United States -- Machine Learning and AI Our team delivers algorithms that ... This role might also be eligible for discretionary bonuses or commission payments as well as ...
Build, deploy, and improve robust machine learning models for product features. * Design both offline and online experiments to test ML product features, and perform data-driven analysis on the ...
Build, deploy, and improve robust machine learning models for product features. * Design both offline and online experiments to test ML product features, and perform data-driven analysis on the ...
Senior Machine Learning Engineer - Healthtech startup
Palo Alto, CA · On-site
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Build, deploy, and improve robust machine learning models for product features. * Design both offline and online experiments to test ML product features, and perform data-driven analysis on the ...
Senior Machine Learning Engineer - Healthtech startup
Palo Alto, CA · On-site
$123K - $168K/yr
Build, deploy, and improve robust machine learning models for product features. * Design both offline and online experiments to test ML product features, and perform data-driven analysis on the ...
Senior Machine Learning Engineer - Healthtech startup
Palo Alto, CA · On-site
$123K - $168K/yr
Build, deploy, and improve robust machine learning models for product features. * Design both offline and online experiments to test ML product features, and perform data-driven analysis on the ...
Senior Machine Learning Engineer - Healthtech startup
Palo Alto, CA · On-site
$123K - $168K/yr
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Senior Machine Learning Engineer
San Francisco, CA · On-site
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Senior Machine Learning Engineer
San Francisco, CA · On-site
$123K - $169K/yr
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Machine Learning Engineer
$150K - $277K/yr
As such, we are seeking candidates with applied machine learning experience and strong software ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...
Machine Learning Engineer
$150K - $277K/yr
As such, we are seeking candidates with applied machine learning experience and strong software ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...
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Quick apply
Machine Learning Engineer - Ads
$205K - $355K/yr
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Machine Learning Inference Engineer
San Francisco, CA · On-site
$401K/yr
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Machine Learning Inference Engineer
San Francisco, CA · On-site
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Machine Learning Engineer
$150K - $277K/yr
Preferred Qualifications MS or PhD in computer vision, computer graphics, machine learning ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...
Machine Learning Engineer
$150K - $277K/yr
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Machine Learning Engineer
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... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...
Machine Learning Engineer
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... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...
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Software Engineering Lead, Machine Learning
Bodega Bay, CA · On-site
$200K - $270K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: * Conceptualize, develop, and deploy machine learning models that ...
Quick apply
Software Engineering Lead, Machine Learning
Bodega Bay, CA · On-site
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Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: * Conceptualize, develop, and deploy machine learning models that ...
Machine Learning Engineer
San Francisco, CA · On-site
$200K - $400K/yr
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Machine Learning Engineer
San Francisco, CA · On-site
$200K - $400K/yr
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Software Engineering Lead, Machine Learning
San Francisco, CA · On-site
$200K - $270K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: * Conceptualize, develop, and deploy machine learning models that ...
Software Engineering Lead, Machine Learning
San Francisco, CA · On-site
$200K - $270K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: * Conceptualize, develop, and deploy machine learning models that ...
Machine Learning FEA Engineer
San Francisco, CA · On-site
$150K - $277K/yr
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Machine Learning FEA Engineer
San Francisco, CA · On-site
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The machine learning models will drive rapid design iterations by assessing potential risks and ... This role may be eligible for discretionary bonuses or commission payments as well as relocation.
Commission Machine Learning Startup information
What is the difference between Commission Machine Learning Startup vs Data Scientist?
| Aspect | Commission Machine Learning Startup | Data Scientist |
|---|---|---|
| Credentials | Degree in Computer Science, Data Science, or related fields; experience with ML models | Degree in Computer Science, Statistics, or related fields; proficiency in programming and data analysis |
| Work Environment | Startup setting, fast-paced, innovative projects, often remote or flexible | Corporate or research environment, collaborative teams, often office-based |
| Industry Usage | Tech startups, AI-focused companies, innovative product development | Tech firms, finance, healthcare, research institutions |
| Search & Comparison Intent | Understanding roles in ML startups, freelance or commission-based opportunities | Career development, skill requirements, industry roles |
Commission Machine Learning Startup roles focus on developing ML solutions within startup environments, often with flexible or freelance arrangements. Data Scientists typically work in established companies, applying statistical and programming skills to analyze data. Both roles require similar credentials but differ in work setting and industry focus.
What are the most commonly searched types of Machine Learning Startup jobs in California?
The most popular types of Machine Learning Startup jobs in California are:
What cities in California are hiring for Commission Machine Learning Startup jobs?
Cities in California with the most Commission Machine Learning Startup job openings:
Machine Learning Engineer
Menlo Park, CA • On-site
Voltai
Full-time
Re-posted 28 days ago
Job description
Job Summary:
Voltai is the leading AI company building agentic systems and frontier foundation models for semiconductor and electronics design. The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while collaborating with engineers and researchers.
Responsibilities:
• Architect and develop high-performance AI systems that combine LLMs, retrieval pipelines, and agentic frameworks tailored to semiconductor and electronics design tasks
• Curate, manage, and optimize large-scale training and evaluation datasets, leveraging both synthetic and human-collected data to support foundation model development
• Train, fine-tune, and deploy foundation models, optimizing for latency, accuracy, and cost across diverse deployment scenarios
• Design cutting-edge retrieval and search algorithms for use in engineering documentation, design schematics, datasheets, and other technical corpora
• Build robust evaluation pipelines to measure model performance across tasks such as code generation, schematic synthesis, and long-context reasoning
• Translate SOTA research into production-ready code, working across the full ML stack from paper to GPU.
• Own strategic technical initiatives, collaborating with customers, engineers, and researchers to solve domain-specific problems with measurable impact
Qualifications:
Required:
• Strong programming expertise in Python, C, or Rust, with a focus on writing performant and maintainable code for large-scale AI systems.
• Proficiency in Python and PyTorch: Strong experience in developing and training models using PyTorch
• GPU Programming with CUDA: Hands-on experience optimizing model training and inference on GPUs using CUDA, including custom kernel development
• Distributed Computing Frameworks: Familiarity with tools like DeepSpeed, Accelerate, Unsloth, or Kubeflow for efficient large-scale model training
• Training and Fine-Tuning: Expertise in fine-tuning and quantizing transformer-based models
• Research to Production: Proven ability to translate academic research papers into scalable, production-ready code.
• Experience in AI Research and Development: Background in AI companies or research labs, contributing to significant machine learning projects.
• Understanding of Model Evaluation and Deployment: Experience in evaluating model performance, deploying models into production environments, and monitoring their performance post-deployment.
Preferred:
• Some background in hardware/electronics, gained through professional, academic, or personal projects
• Contributions to open-source initiatives
• Notable awards or publications in leading journals/conferences
• Experience thriving in a fast-paced, hyper-growth startup environment
Company:
AI models for electronics Founded in , the company is headquartered in , , with a team of 11-50 employees. The company is currently Early Stage.
Voltai is the leading AI company building agentic systems and frontier foundation models for semiconductor and electronics design. The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while collaborating with engineers and researchers.
Responsibilities:
• Architect and develop high-performance AI systems that combine LLMs, retrieval pipelines, and agentic frameworks tailored to semiconductor and electronics design tasks
• Curate, manage, and optimize large-scale training and evaluation datasets, leveraging both synthetic and human-collected data to support foundation model development
• Train, fine-tune, and deploy foundation models, optimizing for latency, accuracy, and cost across diverse deployment scenarios
• Design cutting-edge retrieval and search algorithms for use in engineering documentation, design schematics, datasheets, and other technical corpora
• Build robust evaluation pipelines to measure model performance across tasks such as code generation, schematic synthesis, and long-context reasoning
• Translate SOTA research into production-ready code, working across the full ML stack from paper to GPU.
• Own strategic technical initiatives, collaborating with customers, engineers, and researchers to solve domain-specific problems with measurable impact
Qualifications:
Required:
• Strong programming expertise in Python, C, or Rust, with a focus on writing performant and maintainable code for large-scale AI systems.
• Proficiency in Python and PyTorch: Strong experience in developing and training models using PyTorch
• GPU Programming with CUDA: Hands-on experience optimizing model training and inference on GPUs using CUDA, including custom kernel development
• Distributed Computing Frameworks: Familiarity with tools like DeepSpeed, Accelerate, Unsloth, or Kubeflow for efficient large-scale model training
• Training and Fine-Tuning: Expertise in fine-tuning and quantizing transformer-based models
• Research to Production: Proven ability to translate academic research papers into scalable, production-ready code.
• Experience in AI Research and Development: Background in AI companies or research labs, contributing to significant machine learning projects.
• Understanding of Model Evaluation and Deployment: Experience in evaluating model performance, deploying models into production environments, and monitoring their performance post-deployment.
Preferred:
• Some background in hardware/electronics, gained through professional, academic, or personal projects
• Contributions to open-source initiatives
• Notable awards or publications in leading journals/conferences
• Experience thriving in a fast-paced, hyper-growth startup environment
Company:
AI models for electronics Founded in , the company is headquartered in , , with a team of 11-50 employees. The company is currently Early Stage.