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Remote Machine Learning R Jobs (NOW HIRING)

ManTech International

Machine Learning Engineer

$128K - $214K/yr

General information Requisition # R67616 Locations USA-Remote Work Posting Date 05/19/2026 Security ... Java, R) and core libraries (TensorFlow, Keras, Scikit-learn). * Explore and visualize data to ...

1 point system

Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks ... R * SQL * TensorFlow, Keras, and/or PyTorch * Microsoft Azure cloud platform * DevOps and/or MLOps ...

FloVision Solutions

Machine Learning Engineer

ABOUT FLOVISION FloVision is a remote-first startup focused on improving the food supply chain, starting with protein processing. We design computer vision and machine learning-assisted production ...

FloVision Solutions

Machine Learning Engineer

OR · On-site +1

ABOUT FLOVISION FloVision is a remote-first startup focused on improving the food supply chain, starting with protein processing. We design computer vision and machine learning-assisted production ...

Orchard LLC

Machine Learning Engineer

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical ...

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Remote Machine Learning R information

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$25.5K

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$88K

How much do remote machine learning r jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote machine learning r in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What cities are hiring for Remote Machine Learning R jobs?

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Remote Machine Learning R jobs near you
Infographic showing various Remote Machine Learning R job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 10 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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