ML Engineer – Agents, LLMs
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Job Description
ML Engineer improving post-training, evaluation, and tool-using agents for KIEFER’s sovereign AI infrastructure and enterprise products. Enhancing long-context reliability and production inference.
Responsibilities:
- Run post-training experiments using supervised fine-tuning, preference optimization, reinforcement learning, or other suitable methods
- Improve how agents plan, use tools, manage execution, and recover from errors
- Build benchmarks, verifiers, and diagnostic tools to measure agent performance and identify failures
- Generate and curate training data, including agent trajectories and difficult cases from target workflows
- Evaluate and improve long-context behavior, memory and retrieval interactions, and reliability over multi-step tasks
- Work with ML, Product, and Engineering to improve inference and bring successful experiments into production with clear regression checks
Requirements:
- 3+ years of relevant ML or research engineering experience, with clear technical ownership and measurable results
- Hands-on LLM post-training experience in at least one area: supervised fine-tuning, preference optimization, reinforcement learning, or a comparable method
- Experience building agent systems involving tool use, multi-step execution, and error recovery
- Strong skills in model and agent evaluation, failure analysis, and the creation or curation of training data
- Strong Python, hands-on experience with PyTorch, JAX, TensorFlow, or a similar framework, and solid software engineering skills
- Experience improving or deploying model-backed systems, with an understanding of LLM inference performance and cost
- Reward modeling or verifier-based training
- Long-context training, memory systems, retrieval, or context compression
- Distributed training or high-performance LLM serving
- Experience delivering agents for complex enterprise, coding, or research workflows
Benefits:
- Competitive package aligned with talent benchmarks
- Hands-on work shaping AI capabilities for Kiefer Tech’s products and real-world applications
- Engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products
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