ML Engineer
Posted on:
October 13, 2026
Arbitr
- 6+ years of experience in machine learning, including hands-on work from before the current LLM wave (NLP, deep learning, or predictive modeling)
- Strong proficiency in Python, with deep experience in PyTorch and the Hugging Face ecosystem
- Proven experience fine-tuning open-source language models (Llama, Qwen, Phi, Gemma, Mistral) and taking at least one to production
- Hands-on experience with SFT, LoRA/QLoRA, DPO, or distillation techniques
- Solid understanding of model evaluation, including building benchmarks, choosing metrics, and reading results critically
- Experience with model optimization and serving (quantization, vLLM, TGI, or llama.cpp)
- Experience building classic ML models for scoring, classification, or risk decisions
- Experience with cloud GPU infrastructure on AWS or GCP
- Self-managed and comfortable working in remote, async environments
- Nice to have: Master’s or PhD in ML, Computer Science, Math, or a related field; experience with pretraining or large distributed training jobs
- Nice to have: background in fintech, lending, insurance, or other decision-driven domains; experience deploying models on-prem or on edge devices
- English proficiency (B2 or higher)
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