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# Senior Machine Learning Engineer

- **Company:** Toloka LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Python (Programming Language), Machine Learning, Open Source Technology, Software Engineering, Reinforcement Learning, Large Language Models, Model Validation, Reliability of Systems, Machine Learning Operations
- **Published:** September 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/phpwyvr6uh

## About the Role

* 3+ years of experience in ML: Strong background in model training, fine-tuning, and Reinforcement Learning (RL);
 * 1+ year in Agent Development: Practical experience building, evaluating, and launching autonomous AI agents;
 * Agentic Frameworks: Proven experience working with frameworks such as LangChain, LlamaIndex, or AutoGen;
 * Open-Source LLMs: Practical knowledge of model distillation and adapting open-source models (e.g., Llama, Mistral);
 * Python Mastery: Advanced proficiency in Python with a drive to apply disciplined software engineering standards to ML;
 * End-to-End Ownership: Ability to work across the entire chain, from research to production operations;
 * Language: Fluency in English (B2 or above).

## Description

* LLM QA - the core technology behind Toloka's automated quality-check mechanism. Every annotation flowing through Self-Service is reviewed by an LLM agent we design, train, and operate.
 * Model distillation and fine-tuning - adapting frontier and open-source models to Toloka's tasks to hit the right quality at the right cost.
 * Evaluation, benchmarking, cost modeling, and model selection across providers.

We own the full chain. The same team designs the ML solution, ships it to production, keeps it running 24/7, analyzes the results coming back from real projects, and feeds that signal into the next iteration. No hand-off between research, engineering, and operations - it's all us.

About the Position

As a Senior ML Engineer, you will design, train, and deploy the AI agents that drive our core products. You will focus on end-to-end ML tasks-including fine-tuning and Reinforcement Learning (RL)-to build resilient agentic workflows in Python. You will own the full lifecycle of your models, closing the loop from research and benchmarking to production scaling and monitoring.

What you'll do

 * Train, fine-tune, and distill ML models (including RL approaches) to power autonomous AI agents.
 * Build and operate agentic workflows in Python, handling complex reasoning and hybrid human-expert interactions.
 * Own evaluation and benchmarking, selecting foundational models and establishing cost models.
 * Manage the full ML lifecycle: design solutions, ship to production, and monitor real-time signals.
 * Implement observability metrics tailored for agent logic, model performance, and system reliability.


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