Staff ML Engineer (ML/AI)

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Define and execute the long-term architecture and roadmap for machine learning and generative AI platforms, enabling the rapid, secure, and reliable deployment of advanced models.
• Architect end-to-end AI infrastructure covering model training, fine-tuning, low-latency inference, centralized RAG systems, vector databases, and enterprise evaluation and guardrail frameworks.
• Establish engineering standards across the AI/ML software development lifecycle, including dataset lineage, CI/CD, automated model evaluation, red-teaming, observability, and production monitoring.
• Partner with product, data science, security, and domain experts to translate strategic business and clinical objectives into scalable AI platform capabilities.
• Provide technical leadership through architectural reviews, high-impact prototypes, critical-path development, and strategic coding contributions.
• Mentor senior machine learning engineers and help establish engineering practices that improve technical quality, scalability, reliability, and delivery across teams.
• Serve as a technical anchor across engineering and data organizations, building alignment around complex architectural and technology decisions.

Requirements:

• 8+ years of experience designing and deploying complex ML/AI solutions in mission-critical production environments, with demonstrated technical leadership.
• Advanced software and systems engineering expertise, including Python, RESTful API design, Protobuf, and microservices architectures.
• Strong hands-on experience with production ML/AI infrastructure, including Docker, Kubernetes, container orchestration, and real-time inference services.
• Proven experience designing modern generative AI systems, including RAG pipelines, LLM fine-tuning, vector databases, and robust evaluation and guardrail frameworks.
• Strong knowledge of data-layer technologies, including relational databases, low-latency key-value stores, distributed queueing systems such as Kafka or Celery, and data pipeline orchestration.
• Experience architecting cloud-native systems on AWS or comparable cloud platforms.
• Exceptional communication and strategic problem-solving skills, with the ability to turn ambiguous technical challenges into clear priorities and influence senior stakeholders across engineering, product, and business functions.
• Experience with Java or Kotlin is a plus, particularly for high-performance production systems.
• Experience working with AI/ML systems in regulated or highly sensitive environments, including HIPAA, SOC 2, PHI, or PII, is preferred.
• Experience building internal developer platforms, ML tooling, or infrastructure products adopted by multiple data scientists and engineers is highly valued.
• A collaborative, mission-driven mindset and enthusiasm for working across disciplines with technical and domain experts.

Benefits:

• Annual base salary of $161,000–$221,500, depending on skills, qualifications, experience, location, and other job-related factors.
• Potential eligibility for discretionary bonuses.
• Comprehensive healthcare coverage, including medical, dental, vision, FSA/HSA, life, and disability insurance.
• Access to coaching and therapy services.
• Equity through discretionary restricted stock units.
• Competitive paid time off, including vacation, sick days, and company holidays.
• Paid parental leave.
• 401(k) plan with up to 3% employer matching.
• Monthly technology allowance.
• Well-being perks, community activities, recognition initiatives, and additional employee experiences.
• Remote work environment with opportunities to collaborate across multidisciplinary teams.