ML Engineer – Agents, LLMs

Job not on LinkedIn

🔥 17 hours ago

🇬🇷 Greece – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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KIEFER

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

🏗️ Construction

🏥 Healthcare

📦 Logistics

Construction • Healthcare • Logistics

KIEFER is an energy technology company focused on developing and delivering technologies that improve the production, storage, distribution, or efficiency of energy systems. The company works at the intersection of engineering and energy innovation to provide solutions for utilities, industrial operators, and other energy stakeholders aiming to reduce costs, increase reliability, and lower environmental impact.

📋 Description

• 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