Senior Full-Stack ML Engineer — Healthcare AI, Hybrid

Evinova; Barcelona; Hybrid; EUR 60,000 - 80,000; Full time

Benefits offered by this job

Flexible working arrangements

Opportunity for mentorship and growth

Engaging team environment

Job summary

A pioneering healthcare technology company based in Barcelona is seeking a Senior Full Stack ML Engineer to lead the development of innovative machine learning models targeted at solving complex healthcare challenges. The role demands strong Python skills, experience in data science, and the ability to mentor colleagues. As part of a collaborative team, you will drive digital transformation and engage with various stakeholders to achieve success. This position offers a minimum of three in-office days per week while supporting individual flexibility.

Qualifications

• Degree in Computer Science, Mathematics or similar field.
• Strong experience in data science and production-ready solutions.
• Proficient in Python and data science libraries.

Responsibilities

• Design and implement advanced ML models for healthcare.
• Lead the ML lifecycle from data preparation to deployment.
• Mentor team members on software engineering.

Skills

Python programming

Data science libraries (NumPy, pandas)

Development of Python APIs (FastAPI)

RESTful API design

AWS cloud services

CI/CD workflows

Docker and Kubernetes

SQL

Education

Degree in Computer Science, Mathematics, Physics or related field

Tools

AWS (CDK, EKS, S3)

Graph databases

AI tools and LLMs

Job description

A pioneering healthcare technology company based in Barcelona is seeking a Senior Full Stack ML Engineer to lead the development of innovative machine learning models targeted at solving complex healthcare challenges. The role demands strong Python skills, experience in data science, and the ability to mentor colleagues. As part of a collaborative team, you will drive digital transformation and engage with various stakeholders to achieve success. This position offers a minimum of three in-office days per week while supporting individual flexibility.