About Onwelo
Onwelo is a technology partner that delivers comprehensive services — from strategy and architecture, through implementation, to maintenance — in the areas of digital transformation, data, and automation. The team is over 400 specialists with strong senior-level competencies and 300+ completed projects for large organizations in Poland, Europe, and the USA. Onwelo operates from several Polish cities as well as offices in Germany, Switzerland, and the USA, combining local presence with global reach.
About the project
We are currently looking, for the purpose of building a deployment platform for a healthcare industry client, for an experienced MLOps Engineer who will be responsible for designing, automating, deploying, and maintaining Machine Learning solutions in the AWS cloud environment.
We are looking for someone who combines knowledge of Machine Learning, DevOps, and Cloud Engineering, and who can translate Data Science solutions into scalable production systems.
Your tasks
•Designing, developing, and maintaining MLOps infrastructure in the AWS ecosystem, in particular AWS SageMaker and AWS Machine Learning services
•Building and developing CI/CD processes dedicated to Machine Learning solutions
•Containerizing ML solutions using Docker
•Monitoring and ensuring observability of ML solutions using AWS CloudWatch
•Providing production support for deployed AI/ML solutions, diagnosing problems and optimizing their performance
•Collaborating with Data Science, Software Engineering teams, and other stakeholders to deliver and maintain AI/ML solutions
Who we are looking for
•4–7 years of general engineering experience, including documented practical experience working with AI/ML solutions in production environments
•Practical knowledge of the AWS ecosystem, in particular AWS SageMaker and services supporting the development and deployment of Machine Learning solutions
•Experience designing and implementing CI/CD processes for ML projects
•Good knowledge of Docker and containerization technologies
•Experience managing ML models, their registration, versioning, and experiment tracking
•Knowledge of AWS CloudWatch and system monitoring and observability topics
•Good knowledge of Python and the Git version control system
•Experience deploying and supporting AI/ML solutions in a production environment
What we offer
•Participation in technology projects for global clients
•Work in the growing fields of data technology, artificial intelligence, and machine learning
•As much as 80% of promotions in our company happen internally
•90% of management staff have a technical education
•Access to internal training and development paths
•Participation in team events, company meetings, and Town Halls
•Access to life insurance and private medical care for yourself and your family
•MultiSport card supporting health and fitness
