Chief Machine Learning Engineer
EPAM Systems — Entroncamento, PT
- Published on
About the Role
We are seeking a skilled and motivated Machine Learning Engineer to join our team. In this role, you will play a crucial part in establishing a scalable and efficient pipeline. You will contribute by deploying to Kubernetes clusters and designing the generation pipeline to ensure smooth model implementation.
Responsibilities
- Design the production-grade generation pipeline.
- Address specific business problems using machine learning solutions.
- Handle data collection, cleaning, and preparation for model training.
- Prepare containerized environments for Kubernetes deployment.
- Identify and resolve pipeline performance issues.
- Collaborate with engineers and data scientists to enhance pipeline efficiency and model accuracy.
- Select appropriate machine learning algorithms to build and train models.
- Stay informed about new developments in machine learning infrastructure and deployment techniques.
About the Candidate
Requirements
- 7+ years of machine learning engineering experience focused on classification metrics.
- Leadership background in data science initiatives.
- Background in Python programming and machine learning frameworks like PyTorch and Lightning.
- Familiarity with containerization technologies such as Docker, along with Kubernetes.
- Proficiency in cloud computing platforms like AWS.
- Experience in Databricks.
- Strong analytical and problem-solving abilities.
- Fluency in English at a B2 level or higher.
Nice to Have
- Certifications in machine learning or data science.
- Expertise in diffusion model architectures.
- Familiarity with model deployment tools like Weight & Biases and SageMaker Endpoints.
- Competency in version control systems, including Git.
- Basic knowledge of model compression techniques.
About the Company
EPAM Systems is known for being a leader in the technology and consulting sphere. We offer varied projects that follow engineering excellence standards.
Company Culture and Benefits
- Competitive compensation depending on experience and skills.
- Individual career path and professional growth opportunities.
- Participation in internal events and communities.
- Flexible work hours.
- Opportunity to work on a variety of projects within the company.