Machine Learning Engineer
Stratio is the World’s Leading Real-time Predictive Fleet Maintenance Platform. The company's proprietary technology combines large-scale processing with the latest machine learning techniques to prevent hundreds of thousands of breakdowns from happening every day, thus saving millions of people from the hassle of public transportation delays, postponed deliveries, or late arrival of essential goods. Stratio’s platform enables zero downtime for 5 of the 10 largest transportation companies in the world. Fleet operators in Europe, North America, Asia-pacific, and Latin America trust Stratio’s technology to fully leverage the data under the hood to safeguard operations, and keep customers happy. Stratio’s technology has enabled transportation for 1.3 billion people so far.
The Machine Learning Engineer at Stratio is responsible for collecting, extracting, integrating and cleansing data and productionise machine learning models. For these tasks we use open-source technologies, multiple data sources, machine learning frameworks and services to deliver deeper and larger insights. You will be working with the latest SoA cutting-edge technologies and solve complex data processing problems to help bring predictive insights and detect faults to our clients.
This position is to be part of the Research team which is responsible for research, develop and productionize machine learning models. This is a complex problem and requires a team effort to succeed. The machine learning engineer is in the center of things and interacts with the Data scientists, Data engineers and Data analysts / Automotive experts throughout the process of taking a model to production.
- Build machine learning pipelines, from the base algorithms into a fully productive machine learning model;
- Design solutions and develop machine learning-based applications, services, and APIs to support the machine learning model integration with the Stratio architecture;
- Work with Data Scientists and Data Engineers to build a consistent, reliable and accurate processes to build machine learning models;
- Focus on performance, scalability, resilience, availability and fault tolerance standards;
- Automate monitoring of model predictions quality and explainability based on criteria set by Data Scientists / Analysts;
- Be part of a technological evolution in the adoption of new tools, frameworks and processes to automate, scale and improve our end-to-end quality;
- Be committed to Continuous Integration and Continuous Deployment.
- BS/MS degree in Computer Science, with minimum 2 years of work experience;
- Experience in developing and maintain machine learning models in a real production environment;
- Familiarity with some popular machine learning frameworks, libraries, and platforms like Airflow, MLflow, Kubeflow, Spark ML, Pandas, PyTorch, TensorFlow, Scikit-learn among others;
- Knowledge in distributed processing using Apache Spark;
- Strong programming knowledge in Python;
- Experience with SOLID and Design Patterns of SW development;
- Experience in using databases such as MS SQL, Elasticsearch or other noSQL databases;
- Experience in Continuous Integration and Continuous Deployment processes;
- Comfortable with an Agile methodologies such Scrum and Kanban;
- Creative problem-solving and critical thinking skills, especially around breaking down complex structures into modular solutions;
- Proficiency in English.
- Work experience in at least one of following areas: Anomaly detection, Unsupervised learning or supervised learning;
- Automotive interest and extensive knowledge of the Automotive industry;
- Experience with containerization and orchestration technologies;
- Experience using message brokers such as Apache Kafka.
We expect you:
- Be able to work with minimal supervision;
- Mentor and grow the elements of the team with less experience;
- Work on ways to automate and improve development and release processes;
- Be eager to learn new tools for new problems;
- Ensure that teams follow established processes;
- Keep an eye for possible improvements and identify disruptions in the processes.
What we offer:
- Health Insurance;
- Fringe Benefits Policy;
- Flexible Work Hours - adjust your schedule to your needs;
- Work Setup - remote, hybrid, onsite - if your job can be done remotely, and you prefer to, you’re free to choose;
- Hardware and software for a full remote setup;
- Monthly All-Hands;
- Quarterly Events to discuss Strategy;
- Autonomy and Ownership Culture;
- Continuous feedback culture;
- Innovation Mindset;
- Career Acceleration.
- Remote / Hybrid / Lisbon / Coimbra
We want inspiring individuals in our teams, where age, race, gender, sexual orientation, politics and religion do not matter, and seek to create a tolerant and open space for everyone. We thrive to provide an inclusive and trustworthy environment.
You can find our Culture Manifesto and more team information here.
Take the road with us!