Senior Python Developer / Scientific Coding Specialist (LLM Projects)

Salve.Inno Consulting; Remote; TRY 150,000 - 300,000; Full time

Job summary

A leading AI consulting firm is seeking a full-time contractor for a short-term remote role focusing on LLM projects. You will use your expertise in Python to solve complex problems and work on building high-quality datasets. Ideal candidates have 4+ years of Python experience, strong analytical skills, and can start immediately with flexible working hours. This role requires collaboration with global teams and participating in design and code reviews for scalable applications.

Qualifications

• 4+ years of hands-on Python experience in professional settings.
• Ability to explain logic and document solutions clearly.
• Availability for full-time commitment with 4-hour PST overlap.

Responsibilities

• Build and maintain robust, scalable applications.
• Collaborate with global engineering teams.
• Participate in code reviews and improve code quality.

Skills

Strong proficiency in Python

Problem-solving ability

Analytical skills

Tools

NumPy

SciPy

Pandas

scikit-learn

PyTorch

Job description

Type: Freelance/Contract | Remote | PST overlap required

Fully remote, short-term contract role (5-8 weeks) requiring 40 hours/week with 4 hours of overlap with PST. You will work as a contractor on advanced LLM-focused AI projects for a leading global AI research partner.

About the project

This project supports the development and evaluation of next-generation Large Language Models (LLMs). You will contribute to building high-quality training and evaluation datasets by solving complex problems, writing accurate and efficient Python solutions, and validating model reasoning across scientific and engineering domains. The work is highly analytical, detail-oriented, and directly impacts how modern AI systems reason, code, and solve real-world problems.

Domain tracks

This is a single role with multiple specialization tracks. Candidates will be aligned to one primary track based on background and experience:

• Python / Machine Learning Track - Python-heavy problem solving, ML-focused coding, model-related logic and data workflows

• Scientific Coding - Physics (Computational Physics)

• Scientific Coding - Biology (Computational Biology / Bioinformatics)

• Scientific Coding - Mathematics (Computational / Applied Mathematics)

• Scientific Coding - Chemistry (Computational Chemistry)

Key Responsibilities

• Build and maintain robust, scalable, full-stack applications

• Take part in designing system architecture and engineering best practices

• Write clean, maintainable, testable code

• Collaborate with global engineering teams in agile workflows

• Participate in code reviews and drive improvements in code quality

Requirements

• Strong proficiency in Python with proven problem-solving ability

• 4+ years of hands-on Python experience in professional, academic, or research environments

• Experience solving non-trivial analytical, numerical, or algorithmic problems

• Ability to clearly explain logic and document solutions

• Availability for full-time commitment (40 hrs/week) with 4-hour PST overlap

• Ability to start immediately or within 1 week

• Background aligned with at least one domain track:
  ML / Data Science / Software Engineering or
  Computational Physics, Biology/Bioinformatics, Mathematics, or Chemistry

Nice to have (not mandatory)

• Machine learning or model deployment experience

• Prior work on AI/LLM-related projects

• Peer-reviewed publications (for scientific tracks)

• Experience with scientific Python libraries (NumPy, SciPy, Pandas, scikit-learn, PyTorch, etc.)

Why Join?

• Engagement type: Contractor / Freelancer (no medical or paid leave)

• Duration: 5 to 8 weeks (with potential extension based on performance)

• Commitment: Full-time, 8 hours/day

• Compensation: Hourly (details shared later in the process)

If you meet the criteria and are excited to take on impactful work with flexible hours, we’d love to hear from you, apply now to be considered for this opportunity.