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Remote Machine Learning Ops Engineer Jobs in Alameda, CA

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

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 ...

Lead Machine Learning Engineer (IC)

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

New

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

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 ...

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

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Showing results 1-20

Remote Machine Learning Ops Engineer information

See Alameda, CA salary details

$35.7K

$145.9K

$219.3K

How much do remote machine learning ops engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for remote machine learning ops engineer in Alameda, CA is $145,942.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $175,700.00 per year, depending on experience, location, and employer.
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What cities near Alameda, CA are hiring for Remote Machine Learning Ops Engineer jobs? Cities near Alameda, CA with the most Remote Machine Learning Ops Engineer job openings:

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 9 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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