Senior AI Engineer: Model Fine-Tuning and Evaluation

• Career path
• Strong mentorship and technical growth
• Competitive salary

🏥 Private health insurance

💳 Cobee flexible compensation (transportation, meals, and childcare support)

⏰ Flexible working hours

🏡 Hybrid work model

Qilimanjaro Quantum Tech is a Barcelona-based company building full-stack analog quantum computers. Founded in 2019 as a spin-off from BSC, UB and IFAE, we bring together quantum hardware, control systems and software to make quantum computing useful in practice.

Build Qilimanjaro’s in-house capability to develop company-owned specialist AI models for engineering and quantum-computing workflows. You will adapt existing models using company knowledge and authorized data, establish whether they improve real tasks, and integrate successful results into tools used by engineers and scientists.

You will be an engineer in the AI squad, working across the organization, you will own the technical work from data preparation through fine-tuning and evaluation to practical integration. You will deliver independently within agreed priorities and work with domain specialists to validate results.

Main ownership areas: Responsibilities

• Translate engineering needs into focused experiments with clear baselines, held-out test data and measurable acceptance criteria.
• Build data pipelines for collection, cleaning, labeling and dataset versioning. Track provenance, permitted uses and licensing, and prevent leakage between training and evaluation.
• Fine-tune existing models, including parameter-efficient approaches, choosing methods suited to the task, available data and compute budget.
• Build reusable evaluation tools to measure task accuracy, regressions, cost and latency. Investigate failure modes and compare fine-tuning with retrieval, tool integration or simpler methods.
• Turn validated experiments into tested, versioned components with documented interfaces. Work with the relevant teams on inference, monitoring and maintenance.
• Explain technical choices and limitations clearly, flag delivery risks early, and document experiments so colleagues can reproduce the results.
• Guide the intern through scoped tasks, pairing and code review.

Help build our in-house AI capability alongside the engineers and scientists developing quantum computers. Your work will connect specialist models with real engineering problems, with room to shape the tools and methods we use. We offer technical growth through multidisciplinary work and an established engineering career path.