
Data Scientist Specialist
6 days ago
We are seeking a highly skilled Machine Learning (ML) Engineer to join our Data team. As an ML Engineer, you will be responsible for the end-to-end lifecycle of machine learning projects, from conception and experimentation to model development and deployment in production.
Key Responsibilities:
- Design, build, and maintain robust and scalable data science and ML infrastructure, including compute resources and necessary tools.
- Develop and maintain CI/CD pipelines for ML model deployment and infrastructure changes.
- Ensure the effective utilization of compute resources and the reliability of our ML/AI systems.
- Introduce and evaluate new tools and technologies to enhance our ML/AI capabilities.
- Collaborate with Data Scientists to optimize and productionize their models, focusing on efficient deployment and integration.
- Implement and manage containerization and orchestration for ML workloads.
- Troubleshoot and resolve infrastructure-related issues impacting ML workflows.
- Contribute to best practices for ML engineering and infrastructure management within the team.
- Participate in knowledge sharing and promote awareness of our team's work within the organization.
Required Skills and Qualifications:
- Educational background in computer science, engineering, mathematics or related fields.
- Solid experience (3+ years) in a Machine Learning Engineering or DevOps role with a focus on ML infrastructure.
- Strong programming skills in Python and experience with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, HuggingFace).
- Hands-on experience with containerization technologies (Docker/Podman, container registries), Kubernetes for orchestration, scaling, and management of ML workloads and CI/CD pipelines (e.g., GitHub Actions, GitLab CI), FastAPI.
- Experience with cloud platforms (AWS, Azure) and deploying ML solutions in cloud environments.
Benefits:
- The opportunity to contribute to business activities that are strategically important for Lithuania.
- Free train trips in Lithuania.
- Internal career and professional development opportunities.
- Additional health insurance.
- Accident insurance.
- Additional paid days of leave.
- Flexibility and hybrid work possibility.
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