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Manager Remote Machine Learning Jobs in California

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

With intelligent agreement management, Docusign unleashes business-critical data that is trapped ... Employee divides their time between in-office and remote work. Access to an office location is ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Manage MLOps infrastructure to monitor and optimize models. Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

... remote. What you'll do: * Implement and refine DL pipelines on distributed computing platforms ... Experience managing large datasets, including data storage (such as HDFS or Parquet on S3 ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

Freenome

Senior Machine Learning Scientist

Brisbane, CA · On-site +1

$110K - $150K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

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All JobsManager Remote Machine Learning JobsManager Remote Machine Learning Jobs in California

Manager Remote Machine Learning information

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

AspectManager Remote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; leadership experienceBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote team management, project oversightData analysis, model development, research
Employer & Industry UsageTech companies, AI firms, startupsTech, finance, healthcare, research institutions
Common Search & ComparisonYesYes

The main difference is that a Manager Remote Machine Learning oversees ML projects and teams remotely, focusing on leadership and strategy, while a Data Scientist primarily conducts data analysis and model development. Managers handle project management and team coordination, whereas Data Scientists focus on technical implementation and research.

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 Manager Remote Machine Learning jobs in California? For Manager Remote Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Manager Remote Machine Learning jobs in California look for? The top searched job categories for Manager Remote Machine Learning jobs in California are:
What cities in California are hiring for Manager Remote Machine Learning jobs? Cities in California with the most Manager Remote Machine Learning job openings:
Manager Remote Machine Learning jobs near you
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Posted 29 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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