Senior Machine Learning Engineer

Tamarind Intelligence; Barcelona; Híbrido; EUR 110.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid-remote policy

Offsite team event

Co-working space access

Learning budget

High-end equipment

Office access in Europe

Descripción de la vacante

Tamarind Intelligence is seeking a Senior Machine Learning Engineer to lead production ML and NLP initiatives in a hybrid Barcelona setting. You will transform customer problems into deployable AI solutions, partner with product and engineering, and drive high-quality software practices.

The role emphasizes hands-on model deployment, collaboration, and coaching teammates while engaging in a fast-paced startup-like culture. Hybrid work with core hours supports team alignment.

Formación

• Solid ML foundation with hands-on production experience.
• Background in computer science or related field preferred; industry exp valued.
• Iterative, evidence-based ML development with quick learning.
• Strong stats and NLP model understanding; production readiness.

Responsabilidades

• Own ML initiatives end to end from problem to deployment.
• Evaluate ML/AI tech with a product-focused mindset.
• Collaborate with product managers and engineers to deliver solutions.
• Write clean, maintainable code with strong engineering practices.
• Mentor engineers and share knowledge to raise team ML capability.

Conocimientos

ML engineering

Python

NLP

Production ML

Pair programming

Communication

Educación

Computer science background

Herramientas

PyData ecosystem

MLFlow

Weights & Biases

PydanticAI

PyTorch/TensorFlow

Descripción del empleo

++Senior Machine Learning Engineer - Safety Manager365 (Hybrid - Barcelona)++

SafetyManager365 teams work rapidly, adapt with agility, and stay focused on delivering meaningful solutions. Airlines generate huge volumes of safety reports, operational data and investigations. Our platform helps safety teams analyse that information, identify risks earlier and make better operational decisions. We are driven by the opportunity to solve complex challenges with real impact for our customers and the wider industry.

We are looking for a Senior ML engineer to join our newly established team inside the larger Comply365 group. The ideal candidate would have hands-on experience deploying machine learning models in production and will thrive in a fast-paced, startup-like environment. We are a highly collaborative engineering culture and we write tests first, pair every day and commit directly to trunk. This is a full-time role (40 hours per week) with core hours from 10am to 5pm to ensure strong team alignment and collaboration, while still allowing flexibility outside of those hours. Due to time-zone alignment and business needs, applicants must be able to work on a hybrid basis in Barcelona (3 days in the office, 2 days remote).

Responsibilities:

• Own ML initiatives end to end - from understanding customer problems and designing experiments through to implementation, deployment, measurement and continuous improvement.
• Apply a strong product mindset when evaluating ML and AI technologies, choosing pragmatic solutions that deliver customer and business value over technical novelty.
• Partner closely with product managers and engineers to design and deliver robust, production-ready ML and AI solutions.
• Write clean, efficient and maintainable code, applying strong software engineering practices and maintaining high standards of quality.
• Work collaboratively through regular pair programming, sharing knowledge, supporting others and continuously improving engineering practices.

Qualifications:

• A solid practical foundation in machine learning and software engineering, with at least 8 years of relevant professional machine learning experience, including substantial hands-on expertise building and operating ML products in production.
• Scientific education in computer science, machine learning or a related discipline is welcome, but equivalent industry experience is also valued.
• A pragmatic, iterative approach to ML development - comfortable running small, time-boxed experiments, learning quickly and changing direction based on evidence.
• Excellent analytical skills and practical understanding of machine learning and statistics, with a focus on text-based (NLP) models.
• Superior knowledge of Python and the PyData ecosystem (pandas, scikit-learn, pytorch / tensorflow) as well as MLOps frameworks (MLFlow, Weights & Biases or similar)
• Proven expertise with Large Language Models (LLMs) and developing agentic AI applications, ideally using frameworks such as PydanticAI.
• Extensive hands-on experience designing, building, deploying and operating production ML systems, including data/ML pipelines, model evaluation, observability and productisation in a cloud environment.
• Provide technical leadership for machine learning initiatives, taking ownership from problem definition and experimentation through to production delivery.
• Coach and mentor other engineers, helping to raise ML capability across the team through pairing, knowledge sharing and technical guidance.
• Excellent communication, self-awareness and interpersonal skills. Able to challenge technical ideas constructively, navigate disagreement with confidence and empathy, and build trust across a collaborative engineering team.
• Strong software engineering fundamentals and experience designing and evolving production systems, with the ability to make sound architecture and engineering trade-offs.
• A passion for the aviation industry and a desire to leverage AI technology to drive improvements and innovations in airline safety
• Salary range: €110-€130K annually, depending on experience.
• Annual team offsite and access to our offices in Europe and a co-working space in your location
• High-end equipment to facilitate your best work
• Learning & Development - budget for industry events and professional courses to support your growth
• A hybrid-remote work policy

Your application implies your consent to the processing of your personal data as outlined in our Privacy Policy.