Ta oferta pracy jest już nieaktualna.
Zapraszamy do wysłania życiorysu - skontaktujemy się w przypadku wznowienia projektu lub podobnej oferty.
Zapraszamy do wysłania życiorysu - skontaktujemy się w przypadku wznowienia projektu lub podobnej oferty.
Tasks:
- They are currently working on a project aimed at synthetic dataset generation for testing autonomous driving functions. You will use modern simulation tools based on established game engines and cloud services (AWS). You will join their team in setting up MLOps as a part of the CI/CD pipeline for the autonomous driving stack.
Desired skills & experience:
- University degree in a related field e.g.: Computer Science, Electrical Engineering, Machine Learning, Computer Vision, Applied Physics or Robotics
- Minimum 3 years of Experience in using AWS
- Strong software engineering skills with Python
- Good understanding of Machine Learning
- DevOps experience implementing Continuous Integration / Continuous Delivery pipelines
- Experience working with MLOps tools (e.g., MLflow, Kubeflow, Amazon SageMaker)
- Experience in using AWS services for machine learning, cloud infrastructure & services, monitoring, logging and alerting tools
- Proficiency with Docker
- Genuine interest with robotics, computer simulation and/or autonomous vehicles
- Fluent English
We offer:
- Work with the latest technologies
- Opportunity to contribute to open source
- Opportunity to assume leadership a role in the future
- Salary (up to 30 000 zł on B2B, contract of employment is also possible)
- 26 days off on B2B contract
- Cosy office space at Hala Koszyki, Warsaw
- Private medical care and sports card
- Flexible working hours in hybrid mode (2 days from office, 3 days from home)
- Friendly and team-oriented culture
- More benefits coming soon!
Good to have:
- Experience in team management / tech lead role
- Experience with cloud-native Kubernetes services (e.g., Amazon EKS, GKE, AKS)
- Familiarity with data related Python libraries and frameworks such as TensorFlow, PyTorch, Numpy, Pandas and Matplotlib
