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Remote Xai Jobs (NOW HIRING)

Socket

Sales Development Representative

Our customers - from Anthropic to xAI, and Figma to Vercel - love Socket (just check out their ... Remote-first, with quarterly team off-sites At Socket, we * Pursue Excellence: We set ourselves ...

SpaceX

Accountant, Revenue

Palo Alto, CA · On-site +1

$110K - $155K/yr

ACCOUNTANT, REVENUE xAI was established with a mission to accelerate human scientific discovery. We ... This position is based in Palo Alto, CA, and requires being onsite - remote and hybrid work is not ...

Alinia AI

Applied AI Research Intern

Experience with explainable AI (XAI). Why Join Alinia? * Cutting-edge tech: Work on one of the most important challenges in AI--alignment, safety, and trust * Flexible work: Hybrid or remote work ...

Socket

Tech Partnerships Lead

San Francisco, CA · Remote

Our customers - from Anthropic to xAI, and Figma to Vercel - love Socket (just check out their ... Remote-first, with quarterly team off-sites At Socket, we * Pursue Excellence: We set ourselves ...

Socket

Tech Partnerships Lead

Our customers - from Anthropic to xAI, and Figma to Vercel - love Socket (just check out their ... Remote-first, with quarterly team off-sites At Socket, we * Pursue Excellence: We set ourselves ...

Walmart

Staff, Data Scientist (Pricing)

Sunnyvale, CA · On-site +1

This is a full-time onsite role based in Bentonville, AR or Sunnyvale, CA; remote and hybrid ... Practical experience with Explainable AI (XAI) and communicating complex modelreasoning to non ...

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Infographic showing various Remote Xai job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 100% Remote job distribution.

Junior Computational Biologist (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$30 - $34/hr

Full-time

Re-posted 20 days ago

Job description

Pay Rate Low: 30 | Pay Rate High: 34
A leading biotechnology research organization is seeking a Junior Computational Biologist to support efforts in refining how cellular states are quantified and validated!
Title: Jr. Computational Biologist (Remote Contract)
Location: Remote (Must be available during PST business hours)
Compensation: $30-34/hour + benefits
Contract Duration: 6-12+ months
Job Duties:
This project will focus on benchmarking functional scoring methodologies and improving interpretability of high-dimensional transcriptomic datasets.
The selected candidate will contribute to distinguishing true biological signal from technical variation in large-scale single-cell atlases, directly enhancing the reliability of automated cell-state classification frameworks.
Start Date: July 1, 2026
  • Duration: Through December 18, 2026
  • Commitment: Full-time (100%)
  • Ideal Candidate: Upcoming June 2026 PhD graduate or recent PhD graduate
  • Location: Onsite in South San Francisco, CA preferred; remote within the U.S. considered (must work PST hours)
  • Visa Sponsorship: Not availabl

Key Responsibilities
  • Systematically evaluate and benchmark computational approaches for quantifying phenotype activation across single-cell transcriptomic datasets.
  • Establish rigorous statistical baselines and negative-control frameworks to improve the robustness of automated cell-state classification methods.
  • Develop or refine computational methods to address limitations in current approaches.
  • Design strategies to distinguish genuine biological signatures from stochastic or technical noise.
  • Present findings in internal scientific reviews and contribute to potential conference abstracts or peer-reviewed publications.

Required Qualifications
  • Extensive hands-on experience in single-cell data analysis using Scanpy, AnnData, and Pandas.
  • Strong proficiency implementing statistical and machine learning models using scikit-learn and SciPy.
  • Demonstrated commitment to reproducible research practices and well-organized code.
  • Ability to clearly communicate complex computational concepts to interdisciplinary scientific teams.
  • Master's degree with ongoing PhD pursuit, or recent PhD graduate, in Computational Biology, Computer Science, Machine Learning, or related quantitative discipline.
  • Interest in drug discovery and comfort working in dynamic, research-driven environments.

Preferred Qualifications
  • Background knowledge in cell biology and/or immunology.
  • Experience with hypothesis testing, noise modeling, and benchmarking computational tools.
  • Familiarity with Explainable AI (XAI) approaches or large-scale biological datasets.
  • Demonstrated ability to build or extend novel bioinformatics pipelines.
    INDBH
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