Machine Learning Engineer

Key Skills

Java Programming, Python Programming, SQL, AWS, Machine learning techniques, Apache Airflow, Docker, Lambda

Job Description

• We help people change their lives. BetterHelp is the world’s largest therapy service. We set out on a mission to provide everyone with easy, affordable, and private access to professional counseling: anytime, anywhere. To date, our network of over 20,000 licensed, accredited, and board-certified therapists have assisted more than 1,000,000 people. Every month, our secure website and mobile app facilitate over 5,000,000 messages, chats, voice calls, and video sessions that help people face life’s challenges.
• We’re taking mental healthcare to the next level. We combine clinical care, cutting-edge technology and data-driven product development to constantly learn, iterate, and improve. We are relentless in our pursuit of better, always questioning the status quo and discovering new ways to get things done and serve our members.
• We are a community that grows together - both professionally and personally. Even with our exponential growth, our team is kept agile and nimble, allowing you to have a huge impact and carve your own path from day one. We invest in our team’s well-being and professional development because we know that business and individual growth go hand-in-hand. You will move fast, remain flexible, and be challenged every day. Join us!

What are we looking for?

We are looking for a Machine Learning Engineer to join the data team. We intend to work on a series of interesting ML driven projects. The ideal candidate should have a combination of experience in machine learning, operations research and software engineering.

As an ML Engineer on the team, you will be responsible for building machine learning and optimization models for BetterHelp products. You will also assist Data Scientists in deploying their code into production. You will have a pivotal role in our organization and you will work closely with Data Engineers, Software Engineers, and Product Managers.

This is an exceptional opportunity for those who want to lead machine learning efforts and make an impact while working in one of the fastest growing businesses in the bay area. This role will work closely with the Director of ML/Data Engineering and will have an important role in setting up the direction of the machine learning efforts, hiring successful talent, and mentoring junior data scientists and engineers.

What will you do?

• Build custom ML, optimization and causal inference tools which enable the data scientists, product managers and operations to make more informed decisions
• Partner with the engineer to incorporate the ML model into production
• Design, prototype and productionize scalable machine learning and optimization 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 data scientists to troubleshoot and optimize complex data 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
• Experience integrating machine learning models in production
• Strong background in causal inference and optimization techniques
• Sold background in machine learning model techniques
• Strong knowledge of computer science fundamentals, including object oriented programming, data structures, and algorithms
• Expert in Python and SQL
• Superb written and oral communication skills
• 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)

• M.S. or Ph.D. degree in computer science, computational science, computer engineering, operations research or equivalent
• Experience in reinforcement learning
• Experience working with AWS EMR, Sagemaker or other cloud based platforms
• Experience with Data stores such as S3, Snowflake, and DynamoDB
• Prior experience in production deployments on AWS Lambda, Fargate, EMR, or Airflow
• Experience with development environment and deployments using Docker

Benefits

• Competitive salary & equity compensation
• Excellent health, dental, and vision coverage
• 401k benefits with employer matching contribution
• Ridiculous perks program
• Office in the heart of downtown Mountain View, a three-minute walk from Caltrain
• Commuter benefits, FSA accounts, and Employee Stock Purchase Programs
• Building something that matters - loved by the people and admired by the press
• Any piece of hardware or software that will make you happy and productive
• Awesome people to work with
• Nothing to slow you down
• Helping people live a better life, every day

The base salary range for this position is $140,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2022. Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable for all full-time positions.