Top Tech Jobs & Startup Jobs

Own end-to-end AI data labeling and evaluation programs supporting frontier healthcare models. Responsibilities include designing annotation tasks and rubrics, managing clinician and expert rater workforces, overseeing vendors, building quality-control systems, tracking throughput and costs, and coordinating ML, engineering, clinical, and infrastructure teams. The role manages supervised, audio, conversational, preference, RLHF, and evaluation data pipelines while improving quality and delivery speed.

Build and operate a GPU management and scheduling platform for approximately 30 models across heterogeneous hardware. Responsibilities include metrics pipelines, admission control, autoscaling, cloud orchestration in Python and Go, infrastructure automation, CI/CD, monitoring, security, compliance, and production reliability. The role partners with engineering and research teams, resolves complex operational issues, mentors engineers, and requires in-office work in Gurugram with some California-hours overlap.

Senior Recruiter responsible for full-cycle hiring across sales, technical, and engineering roles. The role emphasizes structured interviewing, quality of hire, candidate closing, hiring-manager partnership, recruiting metrics, process efficiency, and recruiting infrastructure. It is initially remote as a contract position, with potential conversion to a full-time, on-site role in Menlo Park.

Owns the UX and interface design of an internal labeling and annotation tool. Responsibilities include redesigning workflows to improve efficiency and accuracy, prioritizing interface changes, defining performance metrics, applying gamification and behavioral psychology, managing reward and feedback mechanics, and partnering with technical product managers and engineering to deliver improvements.

Own the end-to-end reinforcement learning and on-policy distillation post-training pipeline for healthcare-focused large language models. Design RL methods, build reward models and verifiers, develop conversational healthcare simulations, automate post-training with agents, and conduct rigorous experiments. Collaborate with research, engineering, and clinical teams to improve model reasoning, safety, and alignment.

Own the company’s three-statement financial model, P&L, balance sheet, cash flow, gross margin, COGS, GPU/cloud, headcount, contractor, software, and G&A forecasts. Lead variance analysis, KPI reporting, cost optimization, unit economics, board and investor materials, and financial model reconciliation with accounting, HR, engineering, recruiting, and business teams.

Own the company’s IT and workplace functions, including identity, endpoints, SaaS, networking, security controls, compliance, budgets, facilities, physical security, AV, vendors, and business continuity. Lead and develop the team, establish service levels, automate provisioning and access governance, manage audits, support remote staff, and oversee technology and workplace integration during acquisitions.

Build reliable training, evaluation, deployment, and data-feedback pipelines for a recursively self-improving machine learning system. Design reward and feedback signals, mitigate reward hacking and distribution drift, develop evaluation harnesses, debug model regressions, stabilize non-stationary learning loops, and ship production ML systems. The role requires strong Python and machine learning engineering fundamentals, reinforcement learning knowledge, production experience, and familiarity with feedback-driven systems such as RLHF, RLAIF, active learning, or agent evaluation.

Build tailored demos and prototypes for an agentic AI platform, write code and integrations, configure agent workflows, and lead technical narratives during enterprise sales cycles. Conduct discovery, design solutions, present to clinical and business stakeholders, support pilots, and communicate field insights to Product and ML teams. The role requires strong coding, consulting, presentation, storytelling, and client-facing skills in a full-time Menlo Park office environment.

The Integration Engineer will design and maintain healthcare data integrations, collaborating with teams to optimize performance and improve reliability using Python and various standards.