Job Description
100% remote. Must reside in Bay Area. Must have prior Start Up experience. About the Role We're looking for a Tech Lead Manager (TLM) to own and drive the AI team building the intelligence layer at the heart of our Client's platform. This is a hybrid IC/management role where you'll spend approximately 70% of your time on hands-on technical work and 30% on people management and team leadership. On the technical side, you'll design, build, and ship the models, agents, and ML systems that power Our Client's predictive and prescriptive capabilities—from forecasting workforce demand and flagging burnout risk to orchestrating LLM- driven planning workflows trained on each customer's historical data. You'll write production code, drive architectural decisions across model training, serving, and Tech Lead Manager, AI 1 evaluation, and set the bar for applied ML quality. On the management side, you'll build, mentor, and grow a high-performing team of ML and AI engineers, owning their career development, performance, and day-to-day delivery. The ideal candidate thrives at the intersection of applied ML depth and people leadership—comfortable context-switching between shipping models and coaching engineers. You'll set the technical direction for your team, partner closely with Product, Design, and Data, and ensure your squad delivers AI capabilities that are reliable, measurable, and shipped at a pace that matches our Clients's growth trajectory. What You'll Do Technical Leadership & Execution (~70%) Own the architecture and delivery of AI features end-to-end—from data ingestion and feature engineering to model training, serving, evaluation, and the product surfaces they power. Design and build the systems behind our Client's forecasting, recommendation, and agentic planning capabilities, including LLM-based pipelines, classical ML models, and hybrid approaches trained on per-customer historical data. Drive engineering excellence: lead architecture discussions for model training and inference infrastructure, set standards for offline/online evaluation, experimentation, and responsible AI, and participate in the full ML lifecycle from problem framing through deployment, monitoring, and on-call. Make pragmatic technical decisions that balance model quality, latency, cost, and long-term system health. Leverage modern infrastructure including PostgreSQL, Redis, Kubernetes, vector stores, and streaming technologies to power our Client's real-time AI workflows. Engage in hands-on coding, model development, code reviews, and performance optimizations, setting the standard for applied ML excellence across the team. Tech Lead Manager, AI 2 Champion AI quality—accuracy, calibration, robustness, latency, and the guardrails that make AI outputs trustworthy in an enterprise context. Implement best practices in evaluation, observability, drift detection, and A/B testing to ensure reliability and measurable customer impact. People Management & Team Leadership (~30%) Manage, mentor, and grow a team of ML engineers and applied AI engineers, owning their career growth, performance reviews, and professional development. Conduct regular 1:1s, provide timely and constructive feedback, and create individual development plans for each report. Foster a culture of psychological safety, trust, accountability, and continuous improvement. Own team planning: scope AI work with Product and Design, participate in sprint planning and Agile ceremonies, and remove blockers. Drive hiring for the team—defining roles, conducting interviews, and making hiring decisions to build a world-class AI engineering team. Maintain team health by monitoring workload, preventing burnout, and ensuring sustainable delivery. Cross-Functional Collaboration Partner with Product Managers and Designers to translate product vision into well-defined AI problem statements and technical plans. Communicate progress, model performance, risks, and trade-offs clearly to engineering leadership and non-technical stakeholders. Collaborate across Engineering, Data, and Platform teams to drive alignment on shared data, features, evaluation infrastructure, and serving systems. What We're Looking For B.S. or M.S. in Computer Science, Machine Learning, or a related field, or equivalent experience. Tech Lead Manager, AI 3 7+ years of hands-on software engineering experience with a strong applied ML background—shipping production ML systems, not just prototypes or research. 2+ years of engineering management or tech lead experience, including direct reports, mentorship, and team-level delivery ownership. Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or equivalent)