Senior ML Engineer (ML/AI)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior ML Engineer (ML/AI) based in the United States.

This is a high-impact engineering role focused on building and scaling next-generation AI systems that power real-world healthcare applications. You will design and deploy production-grade machine learning solutions that integrate predictive modeling, natural language processing, and generative AI into scalable platforms. Working at the intersection of research and engineering, you will transform experimental models into robust, high-performance systems used in production environments. The role requires strong expertise in building ML pipelines, distributed systems, and AI-driven microservices. You will collaborate closely with product, data, and engineering teams to deliver reliable, low-latency, and high-availability AI solutions. This is an opportunity to contribute to meaningful, socially impactful technology that improves access to mental health care at scale.

You will be responsible for designing, building, and scaling end-to-end machine learning systems that power core AI capabilities across production environments.

• Design, train, fine-tune, and evaluate ML, deep learning, and generative AI models including LLMs and advanced NLP systems.
• Build and maintain scalable ML pipelines for training, evaluation, and real-time/batch inference.
• Architect and optimize data pipelines for large-scale structured and unstructured datasets, including preprocessing and vectorization.
• Integrate AI models into production microservices with a focus on latency, scalability, and reliability.
• Develop robust evaluation frameworks covering model performance, bias mitigation, alignment, and safety guardrails.
• Optimize models and systems for cost, latency, and efficiency using techniques such as quantization and distillation.
• Collaborate cross-functionally with backend, frontend, and product teams to deliver end-to-end AI features.
• Provide technical leadership through code reviews, architectural guidance, and engineering best practices.
• Mentor junior engineers and contribute to raising the overall ML engineering maturity of the team.
• Contribute to AI roadmap discussions and influence product direction through technical insight.

Requirements:

You bring strong hands-on experience in building and deploying machine learning systems in production, along with deep technical expertise in modern AI/ML architectures.

• 6+ years of experience building and deploying ML/AI systems in production environments.
• Strong proficiency in Python and experience writing production-grade code.
• Experience building and scaling RAG-based systems and working with vector databases.
• Solid understanding of deep learning, NLP, and generative AI models (including LLMs).
• Experience designing and maintaining scalable ML pipelines and MLOps workflows.
• Familiarity with microservices architecture and integration of ML models into production systems.
• Experience working with cloud environments (AWS preferred) and containerization tools like Docker and Kubernetes.
• Knowledge of data processing frameworks and relational or low-latency databases.
• Strong communication skills with the ability to align technical and non-technical stakeholders.
• Ability to balance research experimentation with production reliability and delivery timelines.
• Experience in healthcare or working with sensitive data is a strong plus.

Benefits:

• Competitive base salary with performance-based bonus eligibility
• Comprehensive medical, dental, and vision insurance coverage
• Health Savings Account (HSA) and Flexible Spending Account (FSA) options
• Equity participation through restricted stock units
• Flexible paid time off, including vacation, sick leave, and company holidays
• Paid parental leave
• 401(k) retirement plan with employer matching
• Monthly technology allowance
• Mental health and wellness support programs
• Access to coaching, therapy, and employee well-being resources
• Opportunity to build AI systems with direct real-world social impact in healthcare