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Software Engineer - Materials Science (Remote)

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Not disclosed
Full Time (Remote)
Associate
1 position
Bangladesh

Job Description

  • Role: Software Engineer - Materials Science (Remote)
  • Location: Remote (Work from Anywhere)


Role Overview:

We are hiring for one of our clients, seeking a Scientific Coding - Material science and Python to work on a full-time basis. Turing is building one of the most rigorous STEM AI training datasets in the industry. The SCICode project creates high‑quality scientific coding tasks that are used to train and evaluate frontier AI models. As a SCICode trainer you will directly contribute to AI research by authoring, implementing, and reviewing complex scientific problems across core STEM disciplines.


Key Responsibilities:

• Write scientific problem specifications that include one main problem and at least three logically connected sub‑problems, each building toward the main solution.

• Implement verified golden solutions in Python with complete unit‑test coverage to ensure deterministic behavior.

• Design discriminative test cases that clearly differentiate correct from incorrect model outputs.

• Run QC validation checks on the Turing Central Task Platform, including Tier 1 structure checks and Tier 2 quality rubrics.

• Iterate on tasks based on QC feedback to meet pass@k evaluation criteria across multiple LLM judges such as GPT, Gemini, and Nemotron.


Required Skills & Qualifications:

• A master’s degree or PhD in material science or a closely related field, demonstrating deep domain expertise.

• Strong Python programming skills with experience in scientific computing and the use of libraries such as NumPy, SciPy, or SymPy.

• Ability to write rigorous, well‑posed scientific problems with clear constraints, expected outputs, and deterministic results.

• High attention to detail to meet strict rubrics for well‑posedness, test‑case discriminativeness, scientific correctness, and determinism.

• Prior experience in AI data annotation, research, or scientific writing, and familiarity with LLM evaluation frameworks or coding benchmarks.


More About the Opportunity:

This role offers a unique opportunity to work with a global leader in AI data and research services, contributing to the creation of high‑quality scientific coding tasks that train frontier AI models. The engagement is a contractor assignment with a commitment of 40 hours per week and an eight‑week duration, requiring four hours of overlap with PST.


Equal Opportunity Employer:

We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.


Apply Now!

Requirements

• A master’s degree or PhD in material science or a closely related field, demonstrating deep domain expertise. • Strong Python programming skills with experience in scientific computing and the use of libraries such as NumPy, SciPy, or SymPy. • Ability to write rigorous, well‑posed scientific problems with clear constraints, expected outputs, and deterministic results. • High attention to detail to meet strict rubrics for well‑posedness, test‑case discriminativeness, scientific correctness, and determinism. • Prior experience in AI data annotation, research, or scientific writing, and familiarity with LLM evaluation frameworks or coding benchmarks.

About Company

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This job post was sourced from LinkedIn Jobs While we strive to bring you the latest opportunities, Niyog has not verified this listing and cannot take responsibility for its accuracy or any outcomes related to it. Please review the details carefully and apply at your own discretion.

Job Information

Posted 1 month ago
Job ID 4465230038
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Menlo Park, California

29
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About Company

HireFeed: A QuikHire product. Earn in dollars. On your hours. From wherever. HireFeed is the AI-curated feed of contract, gig, and AI training jobs that pay in USD, built for the people who actually want to work, not the ones writing job descriptions...
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