Machine Learning Engineer

Job summary

We are seeking a Machine Learning Engineer to join our MLOps team, focusing on deploying and maintaining machine learning models in production. This role involves collaboration with data scientists and software engineers to enhance AI-driven solutions.

Qualifications

• Proven experience in deploying machine learning models in cloud environments such as GCP, AWS, or Azure.
• Familiarity with CI/CD pipelines for machine learning, including tools like GitHub Actions and Docker.
• Experience with ML platforms/frameworks such as VertexAI, Kubeflow, or Sagemaker.
• Knowledge of data processing frameworks, particularly Apache Beam/Dataflow, is highly desirable.
• Understanding of model monitoring and maintenance in production settings.
• Experience in performance and cost optimization techniques.
• Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong problem-solving abilities and effective communication skills.

Responsibilities

• Collaborate with data scientists to transition machine learning models from development to production, ensuring optimal performance and scalability.
• Develop and maintain data and model pipelines that integrate with existing systems.
• Design and implement CI/CD pipelines to facilitate the deployment of machine learning models.
• Monitor the performance of deployed models to ensure reliability and quality.
• Work with cross-functional teams to create solutions that align with business needs and best practices in machine learning.
• Continuously enhance infrastructure to support AI model production and delivery.
• Develop MCP servers and A2A agents using the internal framework for managing multi-agent orchestrated deployments.

Skills

• Strong foundation in machine learning and software engineering principles.
• Ability to learn quickly and work collaboratively in a team environment.

Education

• Relevant degree in Computer Science, Data Science, or a related field is preferred.

Tools

• Familiarity with machine learning libraries and frameworks, cloud platforms, and data processing tools.