Location: Remote (Spain-based)
Level: Senior
Type: Full-time

At Nuvolar, we’re driven by purpose, integrity, and the pursuit of excellence, and we’re looking for a Senior Machine Learning Engineer who shares these values to join an ambitious and impactful project in the healthcare industry.

You’ll play a key role in transforming complex data into life-changing solutions. This is more than just a technical role: it’s a chance to make a tangible difference in the way healthcare works, and in people’s lives.

 What You’ll Do

As part of a dynamic, cross-functional team, you’ll be responsible for designing, building, and deploying production-ready machine learning models and robust data pipelines in Microsoft Azure. You’ll collaborate with both technical peers and business stakeholders to develop innovative, data-driven solutions with real-world healthcare applications.

Your main responsibilities will include:

• Develop, train, evaluate, and deploy predictive data models using Python and ML libraries such as Scikit-learn and PyTorch.
• Design, build, and maintain scalable data processing pipelines and data flows using Azure Data Factory (ADF).
• Utilize Azure ML Studio for model experimentation, training, and deployment.
• Work extensively with large datasets, including Parquet files, stored in Azure Data Lake.
• Perform feature engineering and selection to optimize model performance.
• Define and apply appropriate validation metrics (e.g., accuracy, precision, recall, F1-score) to assess model performance and ensure business alignment.
• Collaborate with stakeholders to understand business needs and translate them into technical requirements, even when dealing with ambiguous or non-detailed user stories.
• Effectively communicate technical concepts and model outcomes to both technical and non-technical audiences.
• Contribute to the design and architecture of cloud-based data science applications.
• Manage code and collaborate with the team using Git, and perform tasks using Bash and the command line.
• Develop and deploy serverless components using Azure Function Apps.

✅ What We’re Looking For

We’re seeking someone with strong technical expertise, business acumen, and a proactive mindset who thrives in collaborative environments.

Must-haves:

• 5+ years of experience in data science or ML engineering.
• Solid experience with the Azure cloud ecosystem: ADF, ML Studio, Data Lake.
• Deep Python knowledge and experience with Pandas, NumPy, Scikit-learn, and PyTorch.
• Strong SQL skills and familiarity with data formats like Parquet.
• Proficient with Git, Bash, and working in terminal environments.
• Ability to work independently with minimal direction on complex tasks.
• Excellent communication skills in English – both written and spoken.

Nice-to-haves:

• Experience training or fine-tuning generative models (e.g., LLMs).
• Advanced knowledge of serverless architectures and Azure Function Apps.

 Why You’ll Love Working at Nuvolar

• Impactful Projects: You’ll work on meaningful projects that improve real lives in the healthcare space.
• People-First Culture: We care about our team, support each other, and have fun together.
• Remote-First Approach: Work from anywhere with flexibility and trust.
• Continuous learning – Access training programs, mentorship, and career development opportunities, and an annual budget for professional development.
• Health and wellness perks – Private health insurance and a gym subsidy.
• Great company culture – We organize team events, knowledge-sharing sessions, and fun activities!

The Hiring Process

We like to keep things simple and transparent:

1. HR Interview – A friendly conversation with our HR team to understand your background and career aspirations.

2. Technical challenge – A hands-on task to assess your problem-solving skills.

3. Technical interview – Meet the team and discuss your approach to data engineering.

If you’re ready to take the next step in your career and work on exciting data projects, apply now!

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Nuvolar Works is an equal-opportunity employer and will not discriminate against any applicant based on age, gender, sexual orientation, disability, national origin, race, or religion. Candidates with disabilities are encouraged to apply, and we are committed to providing an inclusive and accessible recruitment process.