Senior Machine Learning Engineer - LLM Systems & Evaluation
Indexed description
Working hours: overlap until 3 pm US EST is required.
Responsibilities
- Own machine learning projects from problem definition through implementation.
- Design and implement evaluation methodologies for AI and machine learning systems.
- Create datasets, benchmarks, and metrics to measure model and product performance.
- Evaluate and improve LLM-based systems, including RAG applications, agents, safety systems, and end-to-end AI products.
- Analyze model behavior, identify failure modes, and recommend practical improvements.
- Build and maintain ML pipelines, tooling, and evaluation infrastructure.
- Collaborate with product, engineering, and research teams to translate business goals into measurable ML objectives.
- Prototype and iterate rapidly to solve business and product challenges.
- 5+ years of experience in Machine Learning Engineering or a related field.
- Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX.
- Experience training, fine-tuning, or adapting machine learning models.
- Experience working with Large Language Models beyond simple API integration.
- Experience evaluating AI systems and translating results into actionable recommendations.
- Experience building and maintaining machine learning systems and pipelines.
- Understanding of retrieval-augmented generation (RAG), agentic systems, and LLM safety concepts.
- Experience designing benchmarks, evaluation frameworks, or automated evaluation systems.
- Experience with distributed training or large-scale model inference.
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
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