Machine Learning Engineer (all genders)

Valantic; Lisboa; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Flexible working hours

Attractive benefits

International, diverse team

Job summary

Valantic Data & AI team in Lisbon designs and implements scalable ML solutions—from architecture and implementation to production integration. You’ll work on diverse client projects across industries and contribute to agile projects.

You’ll collaborate with Cloud, Data, and AI Engineering or Consulting colleagues while shaping technological trends through real client work. The role requires deep Python and ML expertise, experience with cloud ML environments, and a strong foundation in data

Qualifications

• Degree in Computer Science, Informatics, Data Science, Mathematics, or a related field.
• Mid-Level: 3–6 years of professional experience in ML engineering.
• Senior: 6+ years of experience with proven track record designing, deploying, and operating production‑grade ML systems and automated training pipelines.
• Expertise in Python, its ML ecosystem (scikit-learn, TensorFlow, PyTorch), SQL, model training, hyperparameter tuning, feature engineering, Airflow pipelines, MLOps (MLflow, Metaflow), ONNX deployment and model monitoring.
• Experience with cloud ML environments (Azure, AWS), containerized/serverless deployments, IaC, and CI/CD for ML workflows.
• Data & Generative AI: knowledge of data quality, relational/NoSQL databases; GenAI frameworks (LangChain, Spring AI), prompt engineering, semantic search, AI-assisted coding tools.
• Fluent in English.
• Strong team player with intercultural communication, independent and analytical thinker.
• Proactive, pragmatic, and solution-oriented.

Skills

Python

ML frameworks

SQL

Airflow

MLflow/Metaflow

ONNX

Cloud (Azure/AWS)

CI/CD for ML

API & Microservices

English

Education

Degree in CS/ Informatics/ Data Science

Tools

Splunk

Prometheus

Grafana

Git

Job description

• You can look forward to a dynamic, challenging, and diverse work environment in the Data & AI domain, where you’ll contribute to innovative client projects across various industries.
• You’ll be part of a hybrid, international expert team that combines technical with consulting excellence.
• You’ll design and develop scalable Data & AI solutions – from architecture and implementation through to integration into production environments.
• You’ll actively contribute to agile projects, take ownership of subprojects, and collaborate closely with colleagues from Cloud, Data, and AI Engineering or Consulting.
• You can expect diverse challenges, plenty of room for initiative, and the opportunity to shape technological trends through real client projects.

Effective Field

• You can look forward to a dynamic, challenging, and diverse work environment in the Data & AI domain, where you’ll contribute to innovative client projects across various industries.
• You’ll be part of a hybrid, international expert team that combines technical with consulting excellence.
• You’ll design and develop scalable Data & AI solutions – from architecture and implementation through to integration into production environments.
• You’ll actively contribute to agile projects, take ownership of subprojects, and collaborate closely with colleagues from Cloud, Data, and AI Engineering or Consulting.
• You can expect diverse challenges, plenty of room for initiative, and the opportunity to shape technological trends through real client projects.

What distinguishes you

• Degree in Computer Science, Informatics, Data Science, Mathematics, or a related field
• Experience:
  • Mid-Level: 3–6 years of professional experience in ML engineering
  • Senior: 6+ years of experience with a proven track record in designing, deploying, and operating production-grade ML systems and automated training pipelines.
• Expertise in Python, its ML ecosystem (scikit-learn, TensorFlow, PyTorch), SQL, model training, hyperparameter tuning, feature engineering, automated pipelines (Apache Airflow), MLOps frameworks (MLflow, Metaflow), model deployment (ONNX), and model monitoring.
• Experience with cloud ML environments (Azure, AWS), containerized/serverless deployments, infrastructure-as-code, and CI/CD pipelines for ML workflows.
• Expertise in software engineering, API and microservice design, monitoring tools (Splunk, Prometheus, Grafana), and engineering best practices like CI/CD pipelines, Git, automated testing, and agile methodologies.
• Data & Generative AI: Practical knowledge of data quality, relational/NoSQL databases; experience with GenAI frameworks (e.g., LangChain, Spring AI) and techniques like prompt engineering or semantic search; routine use of AI-assisted coding tools.
• Fluent in English.
• Strong team player and intercultural communication skills.
• Independent, structured, and self-reliant working style.
• Pragmatic, solution-oriented, and analytical thinker.

What you can expect

• Professional environment with challenging national and international digital projects for well-known customers and hidden champions;
• A passionate team with a Can-Do Attitude that welcomes you with open arms;
• A modern working environment with a feel-good factor;
• Development opportunities that suit you;
• Flexible working hours, attractive benefits and of course lots of fun.