Machine Learning Engineer

Promptly Health; Portugal; Remote; EUR 45,000 - 70,000; Full time

Benefits offered by this job

Ownership and clear career pathway

Growth opportunity in a fast-growing team

Competitive salary and annual bonus

Equity compensation via ESOP

Annual training allowance

Private health insurance

Home-office equipment allowance

Flexible work schedule

Corporate events and retreats

Job summary

A leading health technology company is seeking a talented Machine Learning Engineer to work on training and deploying models with an emphasis on NLP. The role offers autonomy, growth opportunities, and a competitive salary. Ideal candidates should have a strong foundation in statistical learning and experience in building machine learning systems in production.

Qualifications

• Strong foundation in statistical learning and data science principles.
• Proven experience building and deploying machine learning systems in production.
• Curious about debugging complex systems and exploring model failure modes.

Responsibilities

• Train, fine-tune, and deploy production models, especially for NLP.
• Develop evaluation and monitoring systems for model quality in real time.
• Engineer robust MLOps pipelines for reliability and efficiency.

Skills

Statistical learning

Python

Machine learning

Model interpretability

NLP

Tools

GCP

AWS

Job description

Company Overview

Promptly is building the first patient-centered global evidence network, offering real world data sharing and monetization capabilities. We generate new knowledge from harmonized datasets, augmented with longitudinal patient-reported data and patient-generated digital biomarkers within a secure and privacy-preserving environment. We deliver insights to health systems, payers, and life-science companies in cardiometabolic, oncology, immunology, and more, operating in 10 countries to improve patient care at lower costs.

About the Role

We are looking for a talented Machine Learning Engineer to bridge applied research and production engineering. The role involves the entire lifecycle of models—training, deployment, monitoring, and evaluation—and requires a strong foundation in statistical learning and a keen interest in model interpretability and reliability.

What You'll Work On

• Train, fine‑tune, and deploy production models, especially deep learning and transformer architectures for NLP.
• Develop novel evaluation and monitoring systems to understand model quality and behaviour in real time.
• Translate cutting‑edge research in information retrieval, semantic search, and agent‑based systems into scalable services.
• Engineer robust MLOps pipelines, automating workflows for reliability and efficiency.

You May Be a Good Fit If

• Possess a strong foundation in statistical learning, data science principles, and classical machine learning.
• Have proven experience building and deploying machine learning systems in production using Python.
• Are naturally curious about debugging complex systems and exploring model failure modes and interpretability.
• Can balance research exploration with engineering rigor, maintaining high standards of quality and reproducibility.
• Are a self‑starter, comfortable taking ownership and driving projects forward with autonomy.
• Have a strong interest in applying ML to challenging NLP domains.

Strong Candidates May Also Have

• Experience building and deploying models in a cloud environment (GCP or AWS).
• Deep expertise in fine‑tuning and evaluating models.
• A proven track record of implementing MLOps best practices at production scale.

Position

• Remote‑first
• Full time

What We Offer

• Ownership and a clear career pathway
• Growth opportunity as one of the first engineers on a fast‑growing team
• Competitive salary and annual bonus
• Equity compensation via ESOP for all team members
• Annual training allowance
• Private health insurance and home‑office equipment allowance
• Equal opportunity and inclusive environment
• Flexible work schedule and vacation policy
• Corporate events, all‑hands meetings, and retreats

Recruiting Process

• Initial interview with the manager and team members to introduce Promptly and the role.
• Technical assessment stage with a test task or business case.
• Optional third interview for clarification if required.
• Job offer and acceptance.
• Reference checks may be conducted during final stages.

Data Privacy

Your personal data will be processed for the purposes of managing Promptly’s recruitment activities, including interview scheduling and assessment. It will be shared with Proef, a provider engaged by Promptly to help manage the hiring process. For more information on how Promptly processes personal data and your rights, see Promptly’s Privacy Policy.

By submitting your application, you consent to Promptly/Proef processing your personal data for recruitment purposes and to store such data for up to 12 months, unless an erasure request is received.

By submitting this application, I confirm that all information given is true to the best of my knowledge and that I have not omitted any required facts. I accept that if any information is false, my application may be rejected, and an offer may be withdrawn.

Job Details

Seniority level: Not applicable

Employment type: Full‑time

Job function: Engineering and Information Technology

Industry: Hospitals and Health Care