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Remote Systems Engineer Contract Jobs in California

Space Systems Engineer

Redwood City, CA · On-site +1

$150K - $250K/yr

About the Job We're seeking an experienced Space Systems Engineer to join our team as we move from ... S. commercial remote sensing regulations (NOAA), FCC spectrum licensing processes, and export ...

Senior Systems Engineer

San Diego, CA · On-site +1

$111K - $153K/yr

This position is contingent upon contract award. Key Responsibilities * Collaborate with government customers, stakeholders, and cross-functional engineering teams to define system capabilities and ...

Space Systems Engineer

Redwood City, CA · On-site +1

$150K - $250K/yr

About the Job We're seeking an experienced Space Systems Engineer to join our team as we move from ... S. commercial remote sensing regulations (NOAA), FCC spectrum licensing processes, and export ...

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a cleared MBSE Systems Engineer who is a current Model-Based Engineering practitioner to support a portfolio of Battlespace ...

Social games and community AI can use our onchain tokens for micro-payments, smart contracts for ... For engineers, we value your deep understanding of how bytes work. You are a tool maker, a system ...

Sr. Systems Engineer

Mountain View, CA · On-site +1

$190K - $300K/yr

As a Sr. Systems Engineer at Reliable Robotics, you will be a part of the System Development team ... This role can be remote, or located at our facility in Mountain View, California. Must be willing ...

We are hiring IBM Z Engineer - 100% remote for a Contract position in remote, USA Overview A Linux on Z Engineer to support system administration, configuration, and compliance remediation across ...

Showing results 21-40

Remote Systems Engineer Contract information

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Infographic showing various Remote Systems Engineer Contract job openings in California as of August 2026, with employment types broken down into 85% Full Time, 9% Part Time, 5% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 15 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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