Staff Machine Learning Engineer

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.

As a Staff Machine Learning Engineer at BetterHelp, you’ll join a diverse team of licensed clinicians, engineers, product pros, creatives, marketers, and business leaders who share a passion for expanding access to therapy. And as a mental health company, we take employee mental health just as seriously as we do our mission. We deeply invest in our team’s well-being and professional development, because we know that business and individual growth go hand-in-hand. At BetterHelp, you’ll carve your own path, make an immediate impact, and be challenged every day – with a supportive community behind you the whole way.

BetterHelp is looking for a Staff Machine Learning Engineer to join our growing Data team. In this role, you’ll help drive a range of impactful, ML-driven initiatives that power our products and improve outcomes for our users.

We’re seeking someone who brings a strong combination of machine learning, optimization, and software engineering experience. You’ll be responsible for designing and building machine learning and optimization models, as well as partnering closely with Data Scientists to productionize and scale their work. As a key member of the team, you’ll collaborate cross-functionally with Data Engineers, Software Engineers, and Product Managers, playing a pivotal role in shaping how machine learning is applied across the business.

This is an exciting opportunity for someone who wants to lead and scale ML efforts, work on meaningful problems, and make a real impact while working on a product used by millions globally. You’ll work closely with the Director of ML/Data Engineering and help define the future of our ML platform and capabilities.

• 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

• 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.

Yes. We operate on PST and candidates in any time zone are welcome to apply. We ask employees to travel to our San Jose, CA office up to three times per year plus one company-wide offsite to collaborate in person and strengthen working relationships. Travel expenses are covered and reasonable accommodations are made for those under unique circumstances who cannot travel.

• 6+ years of experience in machine learning
• Proven experience deploying and integrating machine learning models into production systems
• Strong expertise in machine learning techniques, including deep learning, neural networks, statistical modeling, tree-based methods, boosting, regression, and dimensionality reduction
• Extensive experience building personalization and recommendation systems
• Working knowledge of operations research concepts such as mathematical modeling, linear and integer programming, and discrete event simulation
• Familiarity with large language models, fine-tuning methods, and reinforcement learning from human feedback (RLHF)
• Solid foundation in computer science fundamentals, including object-oriented programming, data structures, and algorithms
• Advanced proficiency in Python and SQL
• Excellent written and verbal communication skills
• Experience developing data pipelines and machine learning libraries/tools
• Eagerness to learn and adopt new technologies
• Interest in mentoring junior machine learning engineers and data scientists
• Comfortable working in fast-paced, high-growth, and agile environments