Description

You will design and implement scalable machine learning architectures for production environments, overseeing data pipelines and model integration.

This role is on-site.

Responsibilities

• Design ML platform architectures and production solutions.
• Select and implement algorithms based on data characteristics.
• Integrate models with engineering and data science teams.
• Oversee data pipelines and ensure training data quality.
• Mentor junior members on ML architecture best practices.

Required Skills

• Strong understanding of machine learning concepts and algorithms.
• Proficiency in Python with TensorFlow and PyTorch.
• Experience designing scalable, distributed systems.
• Hands-on work with Git, Jenkins, and CI/CD pipelines.
• Experience with Docker and Kubernetes.
• Familiarity with AWS, Azure, or GCP.
• Ability to translate business goals into technical requirements.
• Master’s degree in Computer Science, Engineering, or related field.

Preferred Skills

• Experience with cloud ML platforms (AWS SageMaker, Azure ML, Google AI Platform).
• Experience working in an Agile development environment.

Key Skills

Education

Master’s degree