ML Engineer – FIXED-TERM CONTRACT / HYBRID / LLMs / Reinforcement Learning

We are looking for ML Engineers (various levels of seniority) to join an exciting European DeepTech start-up in Madrid OR Barcelona. They can offer hybrid working (3 days on-site) within a commutable distance.

They’re a fast-growing AI & quantum computing company that develops cutting-edge software that boosts performance & efficiency.

As an ML Engineer your responsibilities will include:

• Develop & maintain complete machine learning pipelines from gathering & refining datasets to model training, validation, & deployment ensuring robust performance that aligns with project objectives.
• Establish reliable evaluation processes to measure model effectiveness, including statistical validation, reliability assessments, & continuous monitoring.
• Enhance computational efficiency by scaling training & inference workflows, leveraging distributed computing, & improving throughput & latency.
• Refine trained models through advanced tuning approaches such as reinforcement learning, preference optimization, & supervised fine-tuning to boost accuracy & safety.
• Implement optimization & compression techniques to balance speed, accuracy, & resource utilization.
• Collaborate closely with multidisciplinary teams to integrate models into production systems & support data preparation, testing, & monitoring.
• Write maintainable, well-documented Python code, adhering to best practices for testing, version control, & collaborative software development.

As an ML Engineer your skills will include:

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Physics, or a related field.
• Proficient in Python & modern ML frameworks such as PyTorch, with strong familiarity in data handling tools (NumPy, Pandas) & version control systems (Git).
• Deep understanding of language modeling, including training workflows, evaluation metrics, & architecture fundamentals.
• Experience managing & processing large datasets including data cleaning, labeling, & validation.
• Hands-on experience using GPUs, containerized environments (Docker), & cloud or cluster-based job scheduling.
• Ability to interpret academic research, prototype efficiently, & transform ideas into reliable production-ready code.
• Excellent communication skills & a collaborative, solution-focused mindset.

Feel free to also refer someone you may know who could be good for the role. If they are successfully placed, we offer a great referral scheme!

Key words – AI / Machine Learning / LLM / Reinforcement Learning / Python / Pytorch / Git / Docker / Pandas / NumPy

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