Senior ML Platform Engineer

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Overview

Optimize AI is seeking a highly skilled Senior ML Platform Engineer to join our dynamic team. In this role, you will be instrumental in building and enhancing our machine learning infrastructure, enabling teams to deploy and manage model training and inference pipelines efficiently. You will collaborate closely with data scientists, software engineers, and product management to design automated solutions, ensure system scalability, optimize performance, and uphold best coding practices. Your expertise will be critical in paving the path for innovation and excellence in our machine learning initiatives.

Job Responsibilities

• Develop and maintain robust ML platform components, focusing on scalability and performance.
• Implement CI/CD pipelines to streamline the deployment of machine learning models.
• Collaborate with data scientists to facilitate model development and deployment workflows.
• Monitor and troubleshoot ML workflows and underlying infrastructure to ensure reliability.
• Enhance existing systems with new features and improvements based on stakeholder feedback.
• Coordinate training sessions and documentation for team members on best practices and tools.
• Engage in code reviews, providing constructive feedback to promote high-quality code.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• Minimum of 5 years of experience in software engineering, with a focus on machine learning platforms.
• Strong proficiency in programming languages such as Python, Java, or Go.
• Experience with container orchestration tools like Kubernetes and Docker.
• Proficient in cloud services (AWS, GCP, or Azure) and related ML tools.
• Knowledge of machine learning frameworks such as TensorFlow or PyTorch.
• Familiarity with data pipeline tools like Apache Airflow or similar.

Technologies & Tools

The Senior ML Platform Engineer will work with a variety of technologies and tools, including but not limited to Python, TensorFlow, PyTorch, Apache Kafka for messaging, Apache Airflow for workflow management, Docker for containerization, and Kubernetes for orchestration. Familiarity with cloud platforms like AWS, GCP, or Azure will be essential in managing and deploying ML models effectively.

Ideal Candidates

The ideal candidates for this role will possess a strong analytical mindset, combined with a passion for machine learning and automation. They should demonstrate exceptional problem-solving skills and an ability to communicate complex concepts clearly and effectively to both technical and non-technical stakeholders. A proactive approach to collaboration and a keen interest in staying updated with industry advancements will also contribute to their success at Optimize AI.