AI Researcher
IBA ICC MOOT: India National Rounds
contract
Posted on:
Location Type: Remote
Location: United States
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Job Level
Tech Stack
About the role
- Fine-tuning pre-trained LLMs on small to medium datasets (500–20k examples)
- Implementing parameter-efficient fine-tuning (e.g., LoRA-style methods)
- Optimising training for cost and performance
- Running experiments on GPU cloud infrastructure
- Evaluating model performance and tradeoffs (specialisation vs generalisation)
- Deploying fine-tuned models for inference
Requirements
- MSc or PhD student in Computer Science, Machine Learning, AI, or related field
- Alternatively, 6 months of hands-on experience training and fine-tuning deep learning models
- Has worked on LLMs in research or industry
- Has fine-tuned at least one transformer model
- Comfortable working independently
- Interested in applied AI and real-world constraints (cost, latency, memory)
Benefits
- 100% Remote Work: Work from anywhere with flexibility and autonomy
- Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
- International Clients: Collaborate with global organizations and solve real-world challenges at scale
- Urban Sports Club Membership: Supporting your physical and mental wellbeing
- Monthly Bolt Credits: For rides
- Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
fine-tuningparameter-efficient fine-tuningLoRA-style methodsoptimising trainingmodel performance evaluationtransformer modelsdeep learningGPU cloud infrastructureapplied AIcost optimisation
Soft Skills
independent workproblem-solvinganalytical thinking
Certifications
MSc in Computer SciencePhD in Machine LearningPhD in AI