Founding Machine Learning Engineer - Barcelona

Founding Machine Learning Engineer - Barcelona

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Advancing People Multilingual

At a Glance

  • Tasks: Tackle hard machine learning challenges in biology and experimental science.
  • Company: Rapidly expanding SaaS company with a supportive, curious culture.
  • Benefits: Competitive salary, equity, flexible time off, and relocation support.
  • Other info: Join a dynamic team in Barcelona with excellent growth opportunities.
  • Why this job: Make a real impact by building meaningful models that help scientists.
  • Qualifications: Strong machine learning experience and ability to reason from first principles.

The predicted salary is between 60000 - 80000 £ per year.

Are you an experienced fluent English speaking Machine Learner, located in Barcelona or willing to relocate? Our rapidly expanding SaaS client is building an in‑person team in Barcelona, working together in English. They support relocation and visa sponsorship where needed. Their values are simple: stay curious, be kind always, and move with purpose. They care about technical depth, but also about how people work together, learn, communicate, and support each other.

They offer competitive salary, meaningful early‑employee equity, flexible time off, flexible work‑from‑home arrangements, a learning and conference budget, high‑quality equipment, and practical support to help you make Barcelona home if it's not already.

Hard Technical Challenges

The company sits at the edge of machine learning, biology, and experimental science. Some of the hardest problems you'll work on include:

  • Learning from sparse biology: Biological data is noisy, expensive, high‑dimensional, and incomplete. How do we learn useful representations of cellular state from limited experimental data?
  • Building models scientists can trust: Cells contain real biological structure: metabolism, regulation, signalling, transport, and stress responses. How do we combine this knowledge with ML to build models that are predictive and biologically meaningful?
  • Guiding better experiments: Useful models should help scientists understand uncertainty, compare hypotheses, and decide what to test next. How do we evaluate models when there is no clean benchmark for 'understanding a cell'?

The Person

We are looking for someone with strong machine learning judgment and experience building models for difficult real‑world systems. You should be able to reason from first principles about data, models, compute, uncertainty, validation, and product usefulness. You should also enjoy ambiguity, care about scientific truth, and want to build systems that help users make better decisions. We care more about depth, judgment, and evidence of exceptional work than credentials.

You may have PhD‑level training in machine learning, physics, biology, chemistry, applied mathematics, computational biology, or another systems‑oriented discipline. You should have strong foundations in one or more of: applied mathematics, statistics, optimisation, probabilistic modelling, causal inference, dynamical systems, scientific ML, or related areas. You may also be an exceptional applied ML engineer without a PhD, with a track record of building models for complex real‑world systems. Experience with biological data is useful, but not required. What matters most is comfort with natural‑world systems: messy, noisy, sparse, nonlinear, and only partially observed.

Nice to Have

  • Experience with mechanistic models, hybrid ML, Bayesian methods, causal inference, dynamical systems, or uncertainty quantification.
  • Experience designing benchmarks in novel or poorly defined problem spaces.
  • Experience building models that move from research into production or user‑facing workflows.
  • Publications or open‑source work in ML, computational biology, scientific computing, or related areas.
  • Experience in a high‑growth company, deep tech startup, or research‑to‑production environment.

If you have the machine learning experience our client is looking for and ideally experience of being part of start‑up or expanding business, apply now for immediate consideration. You could live in Barcelona now or could be keen to relocate - relocation support and visa sponsorship is available.

Advancing People Ltd is an Equal Opportunities Employer and acts as both an Employment Business and Employment Agency.

Founding Machine Learning Engineer - Barcelona employer: Advancing People Multilingual

Join a dynamic and innovative team in Barcelona, where curiosity and kindness drive our mission to tackle complex machine learning challenges at the intersection of biology and experimental science. We offer competitive salaries, meaningful equity, flexible work arrangements, and a supportive environment that prioritises employee growth and collaboration. With practical relocation support and a commitment to fostering a culture of learning, this is an exceptional opportunity for those looking to make a significant impact in a rapidly expanding SaaS company.

Advancing People Multilingual

Contact Details:

Advancing People Multilingual Recruitment Team

StudySmarter Expert Advice🤫

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We think you need these skills to ace Founding Machine Learning Engineer - Barcelona

Machine Learning
Model Building
Applied Mathematics
Statistics
Optimisation
Probabilistic Modelling
Causal Inference

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