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Hourly Remote Machine Learning Jobs in California

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

Genentech

Machine Learning Engineer

South San Francisco, CA · On-site +1

$168K - $312K/yr

The Machine Learning Engineer sits on the Data Science & Machine Learning Team to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data ...

New

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site +1

$187K - $220K/yr

Develop machine learning models to analyze the distribution of computer vision data. Develop data annotation tools with integrated machine learning models for efficient data annotation. 40 hours/week.

Spotter

Machine Learning Scientist

Culver City, CA · Remote

Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production machine learning models, particularly in areas such as ...

Reddit

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Design, build, and deploy industrial-level machine learning models to solve critical problems in ad ranking, bidding, and optimization. Take full ownership of the ML lifecycle, from ideation and ...

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Hourly Remote Machine Learning information

What is the difference between Hourly Remote Machine Learning vs Hourly Remote Data Scientist?

AspectHourly Remote Machine LearningHourly Remote Data Scientist
Required CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are commonRequires a degree in statistics, data science, or related fields; certifications in data analysis or statistical modeling are beneficial
Work EnvironmentRemote, project-based, often involves developing algorithms and modelsRemote, analytical focus, involves data analysis, visualization, and insights generation
Employer & Industry UsageTech companies, AI startups, research institutionsBusiness, finance, healthcare, tech firms

Hourly Remote Machine Learning professionals focus on developing algorithms and models, often requiring specialized AI knowledge, while Hourly Remote Data Scientists analyze data to generate insights. Both roles are remote, but their core tasks and industry applications differ slightly.

What are the most commonly searched types of Remote Machine Learning jobs in California? The most popular types of Remote Machine Learning jobs in California are:
What are popular job titles related to Hourly Remote Machine Learning jobs in California? For Hourly Remote Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Machine Learning jobs in California look for? The top searched job categories for Hourly Remote Machine Learning jobs in California are:
What cities in California are hiring for Hourly Remote Machine Learning jobs? Cities in California with the most Hourly Remote Machine Learning job openings:
Hourly Remote Machine Learning jobs near you
Infographic showing various Hourly Remote Machine Learning job openings in California as of July 2026, with employment types broken down into 74% Full Time, 13% Part Time, and 13% Contract. Highlights an 100% Remote job distribution.
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 13 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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