Senior/Staff Machine Learning Engineer

What are we looking for?

BetterHelp is looking for a Senior/Staff Machine Learning Engineer to join its data team. BetterHelp intends 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, RL, and causal inference tools which enable the data scientists, product managers, and operations to make more informed decisions
• Partner with the engineers to incorporate the ML models into production
• Design, prototype, and productionalize scalable machine learning and optimization models
• Play a critical role 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.

Can I work remotely?

Yes. We operate in Pacific Time and candidates in any time zone are welcome to apply. We also ask our employees to travel to our Mountain View, CA office up to three times per year and to one company offsite to collaborate in person in order to build better working relationships and experience our in-office culture. Travel expenses will be covered and reasonable accommodations will be made for those under unique circumstances who cannot travel.

Requirements

• 3+ years of experience in machine learning
• Experience integrating machine learning models in production
• Expertise in deep learning, transformer and language models
• 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
• Expert in pandas, numpy, pytorch, keras, tensorflow, statsmodel, ray
• 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
• Ability to work in the US, to travel to our Mountain View, California offices up to three times per year and to an additional company offsite.

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 & compensation
• Excellent health, dental, and vision coverage
• 401k benefits with employer matching contribution
• Unrivaled perks program (including free therapy, UberEats, and more)
• Remote work with regular in-person bonding experiences sponsored by the company
• Office in the heart of downtown Mountain View, a three-minute walk from Caltrain
• Commuter benefits, FSA accounts, and Employee Stock Purchase Programs
• 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

The base salary range for this position is $175,000 - $235,000. In addition to the base salary, this position is eligible for a performance bonus and the extensive benefits listed here (subject to eligibility requirements): Teladoc Health Benefits 2024. 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 to all full-time positions.

At BetterHelp we thrive on difference and individuality, and as part of the Teladoc Health family, we are proud to be an Equal Opportunity Employer. We never have and never will discriminate against any job candidate or employee due to age, race, ethnicity, religion, sex, color, national origin, gender, gender identity, sexual orientation, medical condition, marital status, parental status, disability, or Veteran status.