Senior ML Engineer (LLMOps)

We are looking for an aspiring professional to join our RnD team.

Responsibilities

• Design, build, and maintain production-grade ML systems with a strong focus on Large Language Models (LLMs).
• Own and evolve the LLMOps lifecycle: data preparation, fine-tuning, evaluation, deployment, monitoring, and iteration.
• Develop evaluation frameworks for LLM quality, robustness, and regression tracking.
• Collaborate closely with researchers, product engineers, mathematicians, and infrastructure teams to translate research prototypes into reliable production systems.
• Contribute to architectural decisions around agentic systems, RAG pipelines, and hybrid ML + symbolic components.

Experience

• 3+ years of experience in Machine Learning or Applied AI roles.
• Hands-on experience deploying ML models to production environments.
• Practical experience with LLMs (open-source or proprietary) in real-world applications.
• Experience operating ML systems under production constraints (latency, cost, observability, reliability).

Technical Skills

• Strong Python proficiency; experience with ML frameworks.
• Solid understanding of modern LLM stacks: fine-tuning, inference optimization, RAG, prompt/agent orchestration.
• Experience with MLOps / LLMOps tooling: experiment tracking, evaluation pipelines, monitoring, CI/CD for models.
• Familiarity with containerization and deployment (Docker, Kubernetes or equivalents).
• Experience with cloud or on-prem GPU environments.

Nice to haves

• Experience working in fast-moving startup or R&D-driven environments is a strong plus.
• Understanding of distributed systems concepts is a plus.

Educational Background

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related field (or equivalent practical experience).

Soft Skills

• Proactive mindset to stay updated with the latest advancements in AI.
• Fluent in conversational and written business English (C1+).
• Ability to work collaboratively in cross-functional teams.
• Experience working using Agile framework.

Personal Qualities

• Individual responsibility. You respect key deadlines and pass on the results of your work to your teammates in an appropriate condition.

• Lifelong learning. You recognize areas for growth and proactively learn new skills for your current and prospective areas of responsibility.

• Vision & planning. You can plan your work several weeks ahead and can juggle multiple projects at once. You know when to postpone a task.

• Thoroughness. You cover every important aspect of your task leaving out no crucial detail.

• Proactiveness and initiative. You offer help if you have spare capacity. You take initiative and pitch your own projects to others.

• Critical thinking. You question every judgement, claim or number and can engage in a healthy debate with your teammates.

• Dynamic, out-of-the-box mindset. You can challenge existing ways, abandon well-trodden paths and embrace the new.

Hiring process steps

• Initial Screening Interview (45 minutes)

  With either CHRO or Talent Specialist.

• Test Assignment

  This mandatory assignment takes up to 2 hours to complete, within 24 hours from the start, and is unpaid.

• 1st Technical Interview with our Tech Lead (1 hour)

  Discuss the test assignment, and check Python proficiency.

• 2nd Technical Interview with our LLM Lead (2 hours)

  To check domain specific proficiency.

• Final interview with our CEO (1.5 hours)

  To check values alignment.