Machine Learning Research Engineer (Remote)

About the role

We are seeking a highly capable Machine Learning Research Engineer to join our AI R&D team. You will work on developing and optimizing next‑generation language models for specialized AI applications, handling everything from model training to inference optimization.

Key responsibilities

• Fine‑tune and post‑train open‑source language models.
• Experiment with supervised fine‑tuning, continued pre‑training, distillation, preference optimization, and reinforcement learning.
• Build high‑quality training and synthetic data pipelines, including reasoning and instruction datasets.
• Explore different model architectures, training strategies, and hyper‑parameters.
• Create rigorous evaluation benchmarks and analyze model failures.
• Optimize models for inference latency, memory usage, throughput, and cost.
• Research techniques to transfer capabilities from larger to smaller models.
• Collaborate with AI systems engineers to integrate models into production.
• Reproduce academic research and maintain reproducible experiment tracking.

Required profile

• Strong experience with PyTorch and modern ML frameworks.
• Hands‑on experience fine‑tuning or training language models.
• Deep understanding of transformer architectures.
• Experience with Hugging Face Transformers and related tooling.
• Familiarity with SFT, LoRA/QLoRA, knowledge distillation, or similar post‑training methods.
• Proficient Python programming skills.
• Experience preparing and processing large‑scale datasets.
• Solid knowledge of model evaluation, benchmarking, and experimental design.

Required skills

• Python
• PyTorch
• Hugging Face Transformers
• Transformer architectures
• Supervised fine‑tuning (SFT)
• LoRA / QLoRA
• Knowledge distillation
• Large‑scale dataset processing
• Model evaluation and benchmarking
• Experiment tracking and reproducible pipelines