ML Engineer — Agents & LLMs

Kiefer

United States

Remote

USD 120,000 - 160,000

Full time

14 days+

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Job summary

KIEFER ищет ML Engineer для повышения возможностей агентов и долгосрочного контекста LLM в продуктах компании. Вы будете работать над пост-тренировкой, сбором данных, оценкой, дизайном агентов и инференсом, чтобы повысить надёжность выполнения многошаговых задач в продакшене.

Требуется опыт в ML, владение Python и фреймворками PyTorch/JAX/TensorFlow, а также умение строить и анализировать системы агентов и их производительность.

Qualifications

  • 3+ года опыта в ML или исследовательской инженерии с ощутимыми результатами.
  • Опыт пост-тренинга LLM в одной из областей: supervised fine-tuning, preference optimization, reinforcement learning или эквивалентный метод.
  • Опыт построения агентных систем с использованием инструментов, многошаговым выполнением и восстановлением после ошибок.
  • Сильные навыки оценки моделей и агентов, анализа сбоев и подготовки обучающих данных.
  • Опыт Python, PyTorch, JAX, TensorFlow или аналогичных фреймворков; хорошие инженерные навыки.

Responsibilities

  • Проведение пост-тренинга экспериментов: fine-tuning, преференции, RL или аналог.
  • Улучшение планирования агентов, использования инструментов, управления выполнением и восстановления после ошибок.
  • Сопровождение разработки бенчмарков, валидаторов и диагностических инструментов.
  • Подготовка и курация обучающих данных, включая траектории агентов и сложные случаи.
  • Оценка и улучшение долгого контекста, памяти и взаимодействий с извлечением информации.
  • Сотрудничество с ML, Product и Engineering для внедрения результатов в продакшн с регрессионными проверками.

Skills

Python
PyTorch
JAX
TensorFlow
Software engineering
LLM/Agent systems
Reinforcement learning
Memory/retrieval

Job description

Описание

KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe. We are looking for an ML Engineer to improve the agent and long-context LLM capabilities behind Kiefer Tech’s AI products. You will work hands-on across post-training, data, evaluation, agent design, and inference, with the goal of making multi-step tasks more reliable in production.

Задачи
  • 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.
Требования
  • 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.
What is there for you
  • Compensation: Competitive package aligned with talent benchmarks.
  • Impact: Hands-on work shaping AI capabilities for Kiefer Tech’s products and real-world applications.
  • AI-native environment: Real challenges across model development, evaluation, and production AI systems.
  • Culture: Engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products.
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