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Assistant Remote Machine Learning Engineer 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 ...

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 ...

Liquid XR

Machine Learning Engineer

Los Angeles, CA · On-site +1

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting meaningful signals from multimodal time-series data. This role focuses on building robust, real-time ...

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Infographic showing various Assistant Remote Machine Learning Engineer job openings in California as of June 2026, with employment types broken down into 3% As Needed, 85% Full Time, 7% Part Time, 3% Temporary, and 2% Contract. Highlights an 42% Physical, 2% Hybrid, and 56% Remote job distribution.

Machine Learning Engineer (Remote)

South San Francisco, CA • On-site, Remote

Astrix Inc
Recruiting and Staffing Services • 1 - 5K employees
Learn more about Astrix Incexternal

$55 - $73/hr

Full-time

Re-posted 12 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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