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.
#LI-DNI
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
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- 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
- Understanding of containerization technologies such as Docker, along with familiarity with Kubernetes
- Proficiency in cloud computing platforms like AWS, including S3 and EC2
- Experience in Databricks
- Strong analytical and problem-solving abilities
- Fluency in English at a B2 level or higher
- 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
- Competitive compensation depending on experience and skills
- Variety of projects within one company
- Being a part of a project following engineering excellence standards
- Individual career path and professional growth opportunities
- Internal events and communities
- Flexible work hours