Staff ML/AI Platform Engineer

Who are we and why should you join us?

BetterHelp is on a mission to remove the traditional barriers to therapy and make mental health care more accessible to everyone. Founded in 2013, we are now the world’s largest online therapy service, providing affordable and convenient therapy across the globe. Our network of over 30,000 licensed therapists has helped millions of people take ownership of their mental health and change their lives forever. And we’re not stopping there – as the unmet need for mental health services continues to grow, BetterHelp is committed to being part of the solution.

What are we looking for?

BetterHelp is looking for a Staff ML/AI Platform Engineer to join its data team. BetterHelp intends to work on a series of interesting AI driven projects. The ideal candidate should have a combination of experience in platform engineering, machine learning, and software engineering.

What will you do?

• 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

What will you NOT do?

• You will NOT worry about "runway", "cash left", or "how much time we have until the next round". We have the startup DNA but we're fully backed and funded, all the way to success.
• You will NOT be confined to your "job". You will get involved in product, marketing, business strategy, and almost everything we do.
• You will NOT be bogged down by office politics, ego, or bad attitude. Only positive, pleasure-to-work-with people are allowed here!
• You will NOT get yourself burned out. We work hard but we believe in maintaining a sustainable work/life balance. Really.

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 terraform, 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

Bonus (Great to have, but not required)

• 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