ML Engineering Lead

• Team Leadership: Lead, mentor and develop a team of machine learning engineers, fostering a collaborative and innovative work environment.
• Project Management: Oversee the end-to-end lifecycle of machine learning projects, from concept to deployment, ensuring timely delivery and high-quality outcomes.
• Model Development: Collaborate with data scientists to design and implement robust and scalable machine learning models and algorithms.
• System Architecture: Define and implement the architecture for ML systems, ensuring they are scalable, reliable and efficient.
• Deployment: Oversee the deployment of machine learning models into production environments, ensuring seamless integration and performance.
• MLOps: Develop and maintain ML operations processes, including CI/CD pipelines, monitoring and automated retraining systems.
• Performance Optimization: Optimize ML models and systems for performance, efficiency and scalability.
• Collaboration: Work closely with cross-functional teams, including data science, software development, product management and IT, to define requirements and deliver solutions that meet business and technical needs.
• Innovation: Stay current with the latest advancements in machine learning and AI technologies and drive the adoption of best practices and new techniques within the team.
• Documentation: Ensure comprehensive documentation of models, algorithms, processes and systems for future reference and reproducibility.

• Education: Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.
• Preferred location of working: UK, Portugal , France and/or Spain
• Experience: 5+ years of experience in machine learning, software engineering, or a related field, with specific experience in leading teams and managing projects.
• Technical Skills:

• Strong programming skills in Python, as well as Go, Rust, R, Java or a similar language.
• Strong proficiency in machine learning and deep learning frameworks such as TensorFlow, TensorRT, PyTorch, or scikit-learn.
• Strong knowledge of ML model development, training and deployment processes.
• Knowledge of software development best practices and tooling, including DevOps, version control (e.g., Git), continuous integration/continuous deployment (CI/CD), telemetry and monitoring, containerization (Docker, Kubernetes) and infrastructure as code (IaC).
• Familiarity with relevant tooling such as ClearML for ML lifecycle management.
• Experience with experimentation platforms such as Jupyter Notebooks.
• Knowledge of data engineering concepts and tools for data preprocessing and ETL.
• Experience in getting machine learning products to production.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud), with a focus on Google Cloud.
• Analytical Skills: Excellent analytical and problem-solving skills with the ability to design innovative solutions to complex problems.
• Communication: Strong verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders.
• Language Requirements: Advanced proficiency in Portuguese and English, with proven fluency at the C2 level in both languages.
• Attention to Detail: High attention to detail and a commitment to ensuring the accuracy and quality of work.
• Adaptability: Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.

• An excellent work environment and an opportunity to create a real impact in the world;
• A truly high-tech, state-of-the-art engineering company with flat structure and no politics;
• Working with the very latest technologies in Data & AI, including Edge AI, Swarming - both within our software platforms and within our embedded on-board systems;
• Flexible work arrangements;
• Professional development opportunities;
• Collaborative and inclusive work environment;
• Salary compatible with the level of proven experience.

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