Engineering Director (Product) - Quantum Computing

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AI Summary

Lead and manage engineering teams, drive strategic planning, and provide visibility to decision makers. Define best practices in model experimentation and evaluation. Develop comprehensive project plans and monitor project timelines.

Key Highlights
Lead and manage multiple engineering teams
Drive strategic planning and execution of machine learning model development and evaluation
Provide visibility to decision makers on modelling trends and research directions
Key Responsibilities
Lead and manage multiple engineering teams
Drive strategic planning and execution of machine learning model development and evaluation
Define best practices in model experimentation and evaluation
Develop comprehensive project plans
Monitor project timelines
Technical Skills Required
Machine Learning Model Development Model Evaluation Large Language Models Fine-tuning Evaluation Benchmark Design
Benefits & Perks
Relocation and Visa sponsorship supported
Permanent position

Job Description


Engineering Director (Product)


A fantastic opportunity for a driven Engineering Director to join an International Quantum Computing Leader, overseeing the Product Team based in San Sebastian, Spain.


***This is a Permanent position, with Relocation and Visa's supported if required!***


As an Engineering Director you will

  • Lead and manage multiple engineering teams focused on model development, evaluation, and related activities, ensuring high performance, collaboration, and delivery excellence.
  • Drive strategic planning and execution of machine learning model development and evaluation initiatives, aligning outcomes with company goals and product vision.
  • Influence and provide visibility to decision makers on modelling trends, research directions, and data-driven insights to help define strategic product priorities.
  • Coordinate cross-functionally with Research, Platform, Marketing, Leadership, and other collaborators to ensure integrated execution across model lifecycles and downstream product applications.
  • Define and implement best practices in model experimentation and evaluation methodologies to ensure scalable and reproducible results.
  • Develop comprehensive project plans, including milestones for model releases, evaluation benchmarks, resource allocations, and risk assessments.
  • Monitor project timelines, technical risks, and resource allocation across teams to maintain delivery excellence.
  • Establish, maintain, and evolve evaluation and analytics systems that measure and improve model accuracy, reliability, throughput, and fairness.
  • Report on engineering progress, research insights, and strategic needs to senior leadership; communicate technical findings clearly to both technical and non-technical stakeholders.
  • Demonstrate a data-driven and customer-centric focus in decision making, ensuring solutions are grounded in measurable outcomes and user impact.
  • Evaluate and make key technical decisions, including trade-offs between model complexity vs. efficiency, internal vs. external datasets, and experimental vs. production-ready approaches to align with company objectives.
  • Mentor engineering managers, technical leads, and other developers, fostering professional growth, technical depth, and cross-team collaboration.



Required Qualifications

  • Master’s degree in Computer Science, Engineering, Physics, Data Science, Operations Research, or related field; or equivalent industry experience.
  • 8+ years of hands-on experience in software engineering, data science, or other relevant engineering domains, including model development or analytics.
  • 2+ years of successful leadership experience managing engineering or data-focused teams in a technology-driven environment.
  • Experience with Large Language Models and other advanced ML architectures; techniques including fine-tuning, evaluation, or benchmark design.
  • Solid understanding of modern ML development pipelines, data science practices, and model evaluation frameworks.
  • Exposure to product management, with a strong understanding of lifecycle planning and cross-functional coordination.
  • Demonstrated experience delivering high-quality analytical or model-based products on time and within scope.
  • Excellent leadership skills with the ability to motivate, guide, and develop diverse technical teams effectively.
  • Strong organizational and time-management skills, coupled with a keen eye for analytical and technical detail.
  • Exceptional communication and Fluent in English.



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