Machine Learning Engineer
WFA Digital Insight
The demand for skilled machine learning engineers in the mental health sector is surging, with a 25% increase in job postings over the last year. As companies like BetterHelp continue to expand their online therapy services, the need for professionals who can develop and scale AI-powered experiences is becoming increasingly important. With the global mental health market projected to reach
Job Description
About the Role
The Machine Learning Engineer role at BetterHelp is a unique opportunity to work at the intersection of AI, NLP, and mental health. As a member of the engineering team, you will focus on developing and improving NLP systems and language model-powered experiences that enhance the online therapy platform. Your work will have a direct impact on the lives of millions of people worldwide, providing them with more accessible and convenient therapy options.BetterHelp's commitment to mental health and employee well-being creates a supportive work environment that encourages creativity, innovation, and collaboration. The company's diverse team of licensed clinicians, engineers, product professionals, creatives, marketers, and business leaders share a passion for expanding access to therapy, making it an exciting place to work for those who are driven by a similar mission.
The role involves working closely with cross-functional teams, including product, engineering, and data science, to identify opportunities where AI can improve user experiences and translate business requirements into scalable ML solutions. Your expertise in machine learning, NLP, and large language models will be crucial in designing and implementing evaluation frameworks, building automated testing pipelines, and optimizing inference performance.
What You Will Do
- Develop and improve NLP systems and language model-powered experiences
- Fine-tune and optimize open-source and proprietary language models for domain-specific use cases
- Evaluate model performance and identify opportunities for quality improvements
- Design and implement evaluation frameworks to measure model quality, reliability, and business impact
- Build automated testing pipelines to identify regressions, quality drops, hallucinations, and failure modes
- Develop metrics and monitoring systems to continuously assess model performance in production
- Design and implement guardrails that improve model reliability, safety, and consistency
- Build systems to detect unsafe outputs, prompt injection attempts, abuse patterns, and fraud-related behaviors
- Partner with product and engineering teams to ensure AI systems behave predictably and responsibly
- Optimize inference performance through quantization, distillation, batching, and model serving improvements
- Deploy and maintain production-grade ML systems running on GPU infrastructure
What We Are Looking For
- Strong foundation in machine learning and NLP
- Experience working with language models, evaluating model quality, and implementing guardrails
- Expertise in designing and implementing evaluation frameworks and building automated testing pipelines
- Ability to optimize inference performance and deploy production-grade ML systems
- Excellent communication skills to translate technical concepts clearly to both technical and non-technical stakeholders
- Experience with Excel and other data analysis tools
- Ability to work in a fast-paced environment and collaborate with cross-functional teams
- Passion for expanding access to mental health care and improving user experiences through AI
Nice to Have
- Experience with large language models and their applications in mental health
- Knowledge of AI safety infrastructure and its implementation
- Familiarity with GPU infrastructure and its optimization
- Certification in machine learning or a related field
- Experience working in a remote team environment
Benefits and Perks
- Opportunity to work on a mission-driven project that impacts millions of lives
- Collaborative and supportive work environment
- Professional development opportunities and investment in employee well-being
- Flexible working hours and remote work options
- Access to the latest technologies and tools in AI and NLP
- Competitive compensation and benefits package
- Recognized certification and training programs
- Annual performance reviews and opportunities for career growth
- Health and wellness programs, including mental health support
- Remote work stipend and equipment support
How to Stand Out
- To stand out, showcase your experience with NLP and large language models, and highlight projects that demonstrate your ability to develop and scale AI-powered experiences.
- Be prepared to discuss your approach to evaluating model quality and implementing guardrails, as well as your experience with automated testing pipelines and optimization techniques.
- Make sure your resume and cover letter are tailored to the role, with a focus on your technical skills and passion for mental health and AI.
- Research the company's mission and values, and be prepared to discuss how your own goals and values align with theirs.
- Practice explaining complex technical concepts in simple terms, as you will need to communicate with both technical and non-technical stakeholders.
- Review your portfolio and be prepared to discuss your experience with machine learning, NLP, and large language models, as well as any relevant certifications or training programs.
- Don't be afraid to ask about the company culture, work environment, and opportunities for growth and development during the interview process.
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