ML researcher

Toloka AI creates data that powers leading GenAI models and innovations. It combines experts, crowdsourcing, and a technology platform to teach AI models to reason and evaluate their efficacy and safety.

• Define the multi-quarter strategy and architecture for Toloka’s post-training stack, keeping fine-tuning, RL, and evaluation capabilities ahead of industry trends
• Architect advanced post-training and RL pipelines, including GRPO, PPO/DPO, reward modeling, Process Reward Models, and RLAIF, for platform-wide LLM alignment and agent behavior
• Design and calibrate automated evaluation ecosystems, including human-aligned LLM-as-a-judge frameworks, dynamic benchmarking suites, and regression control setups
• Lead research on model distillation, quantization, context compression, and speculative decoding to optimize latency-cost trade-offs at platform scale
• Architect autonomous guiding agents and tool-use workflows, establishing frameworks for multi-step reasoning, self-correction, and evaluation-driven feedback loops
• Raise the team’s engineering and research standards through architectural design reviews, hands-on mentoring of Senior ML Researchers, and reproducible ML R&D best practices
• Partner with Product and Engineering directors to translate client challenges into scalable platform architecture
• Author research write-ups and blog posts, and deliver external tech talks

• 6+ Years in ML engineering or applied research, including 3+ years leading LLM post-training, fine-tuning, or alignment initiatives at scale
• Deep theoretical and practical mastery of LLM alignment: SFT, LoRA/PEFT, RLHF/RLAIF (GRPO, DPO, PPO), reward modeling, and reasoning-oriented post-training
• Proven experience building evaluation pipelines from scratch, addressing LLM-as-a-judge biases, and calibrating automated evaluations against human gold standards
• Strong proficiency in Python, PyTorch, distributed training frameworks (Deepspeed, Megatron, FSDP), and high-performance inference engines (vLLM, TensorRT-LLM)
• Ability to turn ambiguous technical challenges into robust platform features while balancing advanced research, production reliability, and cost constraints
• Proven experience as a technical leader, mentoring senior researchers or engineers and influencing cross-functional roadmaps
• Fluent spoken and written English (C1), with the ability to explain complex technical concepts to internal teams, external clients, and the research community

• Competitive compensation package including base salary, bonus, and ESOP
• Paid PTO and benefits vary by location
• IT setup and home office allowances