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 – The Recruitment Specialist

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