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Contract Machine Learning Startup Jobs in California

Spotter

Machine Learning Scientist

Culver City, CA · On-site

... 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 ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have ... We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on ...

Adobe, Inc.

Machine Learning Engineer

San Jose, CA · On-site

Good understanding of machine learning, deep learning, or data analytics concepts. * Excellent ... We match the pace, innovation and excitement of a startup, backed by the resources and ...

Adobe

Machine Learning Engineer

San Jose, CA

Good understanding of machine learning, deep learning, or data analytics concepts. * Excellent ... We match the pace, innovation and excitement of a startup, backed by the resources and ...

Jobzhr

Machine Learning Engineer

Pleasanton, CA · On-site

$110 - $150/hr

Contract * W2 position * Work Location: Hybrid type of work in Pleasanton CA. Proficiency in ... Expertise in Python, R, and SQL is required, as well as familiarity with machine learning ...

Goodfire

Machine Learning Engineer

San Francisco, CA

$200K - $400K/yr

About the role We're looking for Machine Learning Engineers to help build our platform for training ... Startup or frontier lab experience in fast-moving teams. Our values Goodfire is looking for ...

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Contract Machine Learning Startup information

What are some common challenges faced by machine learning professionals working on a contract basis at startups?

Machine learning professionals working as contractors at startups often face challenges such as rapidly changing project scopes, limited access to large datasets, and the need to quickly adapt to new tools and frameworks. Startups typically move fast, so contractors must be comfortable with ambiguity and prioritize delivering value in short timeframes. Additionally, they may need to collaborate closely with cross-functional teams, such as product managers and engineers, to ensure that machine learning solutions align with business goals.

What is the difference between Contract Machine Learning Startup vs Data Scientist?

AspectContract Machine Learning StartupData Scientist
CredentialsRelevant degrees, certifications in ML/AITypically similar credentials, often with advanced degrees
Work EnvironmentProject-based, startup setting, flexible hoursOffice or remote, corporate or research settings
Employer & IndustryStartups in tech, AI, or data-driven sectorsVaried industries including tech, finance, healthcare
Search & Comparison IntentUnderstanding contract roles in ML startupsExploring data science career options

Contract Machine Learning Startup roles focus on short-term, project-based work within startup environments, often requiring specialized skills in ML and AI. Data Scientists typically work in more established companies or research settings, with similar credentials but often in a full-time capacity. Both roles demand strong technical backgrounds, but contract roles offer flexibility and varied projects, while Data Scientists may have more stability and broader responsibilities.

What are the key skills and qualifications needed to thrive in a contract machine learning startup role?

Success in a Contract Machine Learning Startup role generally requires expertise in machine learning algorithms, data analysis, and a solid background in computer science or related fields. Familiarity with programming languages such as Python or R, experience with ML frameworks like TensorFlow or PyTorch, and knowledge of cloud platforms (e.g., AWS, GCP) are typically expected. Strong problem-solving, adaptability, and effective communication help professionals collaborate with clients and respond to rapidly changing project requirements. These skills and qualities are vital to deliver innovative, scalable solutions in fast-paced, outcome-driven startup environments.

What is a contract machine learning startup?

A Contract Machine Learning Startup is a company or team that provides machine learning solutions and services to clients on a contract basis. Instead of developing their own products, these startups typically work with other businesses to build custom machine learning models, analyze data, and help integrate AI technologies into existing workflows. They may offer expertise in areas such as natural language processing, computer vision, or predictive analytics, and usually operate on short-term or project-based contracts. This approach allows client companies to access specialized knowledge without hiring full-time data scientists or engineers.
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 are popular job titles related to Contract Machine Learning Startup jobs in California? For Contract Machine Learning Startup jobs in California, the most frequently searched job titles are:
What job categories do people searching Contract Machine Learning Startup jobs in California look for? The top searched job categories for Contract Machine Learning Startup jobs in California are:
What cities in California are hiring for Contract Machine Learning Startup jobs? Cities in California with the most Contract Machine Learning Startup job openings:
Contract Machine Learning Startup jobs near you

Mid-Level Machine Learning Engineer

TetraMem - Accelerate The World

San Jose, CA • On-site

Full-time

Re-posted 23 days ago

Job description

Job Summary:
TetraMem is a company focused on accelerating the world through innovative technology, and they are seeking a Mid-Level Machine Learning Engineer to develop and optimize machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, providing mentorship, and researching state-of-the-art ML techniques to enhance model efficiency.
Responsibilities:
• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
Qualifications:
Required:
• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
• Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
• Ability to work independently and collaboratively in a fast-paced startup environment.
• Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.
Preferred:
• Understanding of ML compiler and runtime design.
• Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
• Familiarity with hardware acceleration techniques.
• Experience in embedded system development.
Company:
TetraMem is developing cutting-edge analog computing solutions for AI applications, offering exceptional performance with ultra-low power consumption. Founded in 2018, the company is headquartered in Newark, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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