Summary

We are seeking a Machine Learning Engineer to join our team! Our Machine Learning Engineers collaborate closely with Data Scientists and other engineering teams to design, implement, and maintain systems that operationalize and scale our data and machine learning pipelines. Expertise in machine learning operations and cloud infrastructure will be crucial in ensuring the successful deployment and management of our production machine learning systems. The ideal candidate will have a passion for cutting-edge technology, complex problem-solving, and delivering high-quality solutions.

Responsibilities

• Collaborate with Data Scientists and product teams to understand user stories and convert them into technical requirements for machine learning solutions.
• Design, build, and deploy production machine learning systems on AWS cloud infrastructure.
• Develop and maintain robust data and machine learning pipelines, ensuring scalability, reliability, and efficiency.
• Implement and optimize monitoring, logging, and alerting systems to ensure the health and performance of deployed machine learning models.
• Work closely with DevOps and infrastructure teams to ensure seamless integration and deployment of machine learning pipelines.
• Automate and streamline the end-to-end machine learning workflow, including data ingestion, feature engineering, model training, evaluation, and deployment.
• Implement best practices for version control, model reproducibility, and model deployment.
• Collaborate with cross-functional teams to identify and address performance bottlenecks, scalability challenges, and data quality issues.
• Continuously evaluate and adopt emerging technologies and tools to improve the efficiency and effectiveness of machine learning operations.

Qualifications

• 1-3 years of relevant work experience in ML, including designing, building, and deploying production machine learning systems.
• Strong expertise in deploying machine learning models on AWS cloud infrastructure.
• Proficiency in Python and SQL for data manipulation, analysis, and model development.
• Strong knowledge of Linux, Docker, and Kubernetes for containerization and orchestration of machine learning applications.
• Strong knowledge of PySpark, Airflow, and data pipelines; strong knowledge of Sagemaker and machine learning pipelines.
• Passion for learning and staying updated with the latest advancements in machine learning, MLOps, and cloud technologies.
• Excellent communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
• Bachelor's degree in Computer Science, related field, or equivalent experience.
• Familiarity with Computer Vision, NLP, or Reinforcement Learning is a plus.
• Experience working at a health system or healthcare technology company is preferred.
• Experience working at a software as a service (SaaS) company is preferred.
• Experience working in a high-growth environment is preferred.