(Senior) ML Ops Engineer

Continental; Lousado; Presencial; EUR 40 000 - 60 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Challenging international work environment

Flexible working model

Continuous personal development opportunities

Resumo da oferta

Continental is hiring a MLOps Engineer for their Digital Solutions Department. You will design, deploy, and maintain robust ML pipelines, ensuring seamless model integration into production environments. Collaborating with cross-functional teams, you will power AI-driven insights in connected mobility.

The ideal candidate has an academic degree in Computer Science or related fields, over 3 years of MLOps experience, and strong programming skills in Python and SQL. Benefits include a flexible working model and continuous development opportunities.

Qualificações

• 3+ years of professional experience as a MLOps Engineer.
• Strong programming skills in Python and SQL.
• Expertise in CI/CD and automation tools.

Responsabilidades

• Design and manage CI/CD pipelines for ML models.
• Build and maintain scalable ML infrastructure.
• Automate deployment, monitoring, and rollback processes.
• Implement monitoring and feedback loops for model performance.
• Collaborate with data scientists and engineers.

Conhecimentos

Programming skills in Python

Strong in SQL

CI/CD expertise

Containerization (Docker, Kubernetes)

ML model deployment

Knowledge of cloud platforms (AWS, Azure)

Monitoring tools expertise (Grafana)

Workflow orchestration (Airflow)

Agile project management methods

Formação académica

Academic degree in Computer Science, IT, Engineering, Mathematics or related field

Ferramentas

MLflow

SageMaker

GitHub Actions

Descrição da oferta de emprego

Job Description

Join Continental’s Digital Solutions Department as a MLOps Engineer

In Digital Solutions, we drive innovation for connected mobility and deliver cutting‑edge digital products to our global fleet customers. As a MLOps Engineer, you will be at the forefront of transforming machine learning into scalable, production‑ready solutions.

You will design, deploy, and maintain robust ML pipelines, ensuring seamless integration of models into production environments and optimizing their performance at scale. Working closely with Data Scientists, Data Engineers, and cross‑functional teams, you will enable AI‑driven insights that power smarter, safer, and more efficient mobility worldwide.

Main responsibilities:

• Design and manage CI/CD pipelines for ML models from development to production;
• Build and maintain scalable ML infrastructure on cloud platforms using infrastructure‑as‑code;
• Automate deployment, monitoring, and rollback processes for reliability and reproducibility;
• Implement monitoring and feedback loops for model performance and continuous improvement;
• Collaborate with data scientists and engineers to integrate ML models and standardize workflows;
• Provide technical leadership and mentorship, fostering knowledge sharing and best practices.

Benefits

Our offer:

• Integration in a challenging and international work environment;
• Flexible working model;
• Agile and collaborative working style;
• Continuous opportunities for personal development and learning.

We are committed to fostering a workplace where everyone feels safe, respected, and valued. All kind of applications are welcome.

Qualifications

• Academic degree in Computer Science, IT, Engineering, Mathematics, or related field;
• >3 years of professional experienceas a MLOps Engineer;
• Strong programming skills in Python and SQL;
• Expertise in CI/CD and automation tools (e.g., GitHub Actions);
• Proficiency in containerization and orchestration (Docker, Kubernetes);
• Hands‑on experience with ML model deployment and lifecycle management (MLflow, SageMaker);
• Good knowledge of cloud platforms (AWS or Azure) and infrastructure‑as‑code practices;
• Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow);
• Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns);
• Experience with Agile project management methods (Scrum, Kanban);
• Experience working in an international team (desirable);
• Proficient English language skills (spoken / written).