Top Tech Jobs & Startup Jobs

Leads global data operations for robotics and AI training datasets, overseeing collection, annotation, quality control, delivery, vendors, budgets, compliance, and process scaling. Builds and manages distributed teams, establishes operational KPIs, coordinates with clients and technical teams, and ensures training-ready multimodal data meets quality and regulatory standards.

Own the architecture and evolution of large-scale storage systems, including data organization, partitioning, indexing, access patterns, durability, performance, and cost efficiency. Design self-service storage interfaces, optimize I/O and data paths, lead migrations and adoption across teams, and quantify production improvements. The role requires strong cross-functional communication, product judgment, and experience operating reliable storage infrastructure.

Develop and deploy machine learning systems that recover metrically accurate 3D human body and hand motion from egocentric video. Responsibilities include pose modeling, camera calibration, multi-view geometry, temporal consistency, annotation and evaluation tooling, large-scale production inference, and human-to-robot motion retargeting. The role combines computer vision, deep learning, robotics, and real-world multi-camera capture systems.

Develop and train learning-based policies for robotic manipulation and embodied tasks using imitation learning, reinforcement learning, diffusion policies, and VLA models. Design data collection and training pipelines, deploy policies on physical robots, evaluate robustness and generalization, debug real-world performance, analyze failures, and improve models and datasets. Collaborate with infrastructure, simulation, and data teams to advance robot learning research.

Research and develop embodied AI systems, including VLA and world models, for physical robots. Responsibilities span multimodal model training, large-scale robotics data pipelines, distributed optimization, deployment, real-world testing, debugging, and performance improvement. The role integrates perception, control, long-horizon planning, robot-environment interaction, and foundation-model research across the full lifecycle from data collection through deployment.

The Vice President of Finance will build and lead the company’s finance function, overseeing financial strategy, FP&A, budgeting, forecasting, cash management, accounting, controls, fundraising, investor relations, and IPO readiness. This hands-on executive will advise the CEO and Board, establish scalable systems and processes, manage external financial partners, and gradually build the finance organization as the company grows.

Lead cross-team improvements to production workflows by identifying bottlenecks, prioritizing business-impacting changes, and implementing improvements across infrastructure, services, tooling, and practices. Establish performance baselines for lead time, throughput, quality, and cost, then validate and scale successful solutions. The role requires strong software architecture, production systems ownership, communication, product judgment, quantitative analysis, and hands-on implementation.

Own end-to-end robotics data collection and annotation projects, translating client AI and robotics requirements into precise specifications. Coordinate engineering, algorithms, data operations, and annotation teams across global regions. Monitor production quality, SLAs, costs, timelines, and data pipelines while establishing validation and spot-check systems. Identify workflow bottlenecks and partner with software teams to automate processes. The role requires project management experience in AI data services, autonomous driving, robotics, or high-throughput data operations, plus strong technical and cross-functional communication skills.

Build and deliver high-quality multimodal robotics datasets for Embodied AI and World Model teams. Responsibilities include translating research requirements into dataset specifications, planning scene distributions, orchestrating simulation-based data synthesis, writing Python and Bash automation, curating and validating large-scale datasets, packaging data into standard formats, and establishing feedback loops between data quality and model performance. The role requires close coordination with clients, algorithm researchers, and platform teams.

Own customer-facing AI, robotics, and autonomous driving projects from discovery through delivery. Translate technical and data requirements into scalable solutions, define workflows and project plans, coordinate internal and external stakeholders, resolve risks, and ensure quality delivery. Support technical proposals, statements of work, pricing, account expansion, and product feedback while building long-term customer relationships.