Responsibilities
- Design, prototype and productionize scalable AI/machine learning models
- Play a critical in setting up the best practices in machine learning, setting direction of the machine learning platform
- Develop frameworks, pipelines, libraries, utilities and tools that process massive data for ML tasks
- Partner with ML engineers and data scientists to troubleshoot and optimize complex ML pipelines
- Work with product managers and business partners to gather requirements for machine learning models
- Build model deployment platform that can simplify implementing new models
- Build end-to-end reusable pipelines from data acquisition to model output delivery
- Mentor and guide junior data scientists to deploy their models into production
- Design & Build ML (engineering) solutions that unlock new ML modeling capabilities for BetterHelp
Requirements
- 3+ years of experience in machine learning platform systems
- Experience with autoscaling, and autoscaling such as load balancing
- Solid understanding of distributed computing and proven experience with them
- Superb written and oral communication skills
- Experience integrating ai/machine learning models in production
- Strong background in shell or bash scripting
- Experience building CICD pipelines
- Experience with infrastructure as service tools such as terrafrom, cloud formation
- Experience working with AWS Lambda, ECS, ECR, Sagemaker or other cloud based platforms
- Prior experience in production deployments on AWS Lambda, Fargate, EMR, or Airflow
- Experience with development environment and deployments using Docker
- Strong knowledge of computer science fundamentals, including object oriented programming, data structures, and algorithms
- Experience in writing data pipeline and machine learning libraries and utilities
- Willingness to learn new technologies
- Willingness to mentor junior ml engineers and data scientists
- Comfortable in a high-growth, fast-paced and agile environment
Nice to Have
- Experience with building and training machine learning models
- Experience hosting open source AI models and LLMs
- Experience working and productioning feature stores
- Experience with Data stores such as S3, Snowflake, and DynamoDB
Benefits
- Remote work with regular in-person bonding experiences sponsored by the company
- Competitive compensation
- Holistic perks program (including free therapy, employee wellness, and more)
- Excellent health, dental, and vision coverage
- 401k benefits with employer matching contribution
- The chance to build something that changes lives – and that people love
- Any piece of hardware or software that will make you happy and productive
- An awesome community of co-workers
Work Arrangement
Hybrid — San Jose, CA
Additional Information
- Candidates in any time zone are welcome to apply
- Employees are asked to travel to the San Jose, CA office up to three times per year plus one company-wide offsite
- Travel expenses are covered
- Reasonable accommodations are made for those under unique circumstances who cannot travel
