AIML Engineer

Preferred experience:
AWS bedrock LLMs LLMOps Computer Vision Motion Capture

Info Needed to Submit: Resume email candidate blurb MM/DD of birth

Job description:

Responsibilities:

• Build and maintain scalable infrastructure for machine learning model & pipeline deployment including containerization & orchestration.
• Develop and maintain scalable & secure REST APIs for serving multiple machine learning models to various users.
• Collaborate with data scientists and software engineers to ensure seamless integration of ML models into our systems.
• Design and optimize data pipelines data storage and data processing systems to support the training and inference processes of machine learning models.
• Build and maintain data and model dashboards to monitor model performance and health in production environments.
• Collaborate with crossfunctional teams to identify and address data quality data governance and security considerations in the context of ML operations.
• Monitor model performance and health in production environments establishing and maintaining appropriate monitoring and alerting mechanisms.

Requirements:

• Required
  • Bachelors degree in Computer Science Data Science or a related field. A Masters or Ph.D. degree is a plus.
  • 5 years of handson experience in ML operations ML engineering or related roles.
  • Experience with AWS & Databricks cloud platforms specifically AWS Sagemaker AWS Jumpstart & AWS Bedrock.
  • Experience with REST API development AWS Networking Protocols
  • Solid understanding of infrastructure components and technologies including containerization (e.g. Docker) and CI/CD pipelines
  • Strong knowledge of software engineering principles and best practices including version control code review and testing.
  • Excellent problemsolving skills with the ability to analyze complex issues and provide innovative solutions in a fastpaced environment.
  • Strong communication and collaboration skills with the ability to work effectively with crossfunctional teams and stakeholders.
• Preferred
  • Familiarity with load balancing EKS (Kubernetes) & latest serving ML Model Serving Techniques (ex. NVIDIA Triton).
  • Familiarity with the Hugging Face Diffusers Library