Software Engineer, Fleet Simulation (Core Data Science)

Zoox is building the world's most advanced self-driving hardware and software solution, and nearly every part of it depends on moving data reliably. Sensor frames to perception, planner decisions to vehicle controls, telemetry to the cloud, and remote operator video back down again. All of it crosses process, host, and network boundaries under hard latency and reliability budgets, on a vehicle that has to keep working when a link degrades or a network gets congested. The Software Core Connectivity team owns that data path end to end: in-vehicle messaging (pub/sub, RPC, inter-process and inter-host transport), the vehicle's internal network, and vehicle-to-cloud connectivity. It also owns the transport and serialization abstractions the rest of the software organization builds on. Every one of those paths crosses a team boundary, so the work happens alongside firmware, product security, simulation, manufacturing, and IT, and those partners rely on this team for transport and networking depth to achieve their goals. As the team leader you will own the roadmap and the release commitments, and you will spend a real share of your time in those partnerships. In this role, you will: Own the roadmap, staffing, and release commitments across the team's messaging, in-vehicle network, and cloud connectivity work. Lead and grow a team of software engineers, run their performance and promotion cycles, and hire into the gaps. Represent the team in cross-functional programs across firmware, product security, simulation, fleet operations, and infrastructure, and build the relationships that keep shared work moving. Set the technical bar. Make the architecture calls stick, and make sure the abstractions the team ships are ones other teams want to build on. Balance interrupt-driven reliability work against long-horizon architecture, and be explicit with partners about the tradeoff. Qualificati

At Zoox, we have set the goal to provide our customers with the highest level of safety while using our fully autonomous vehicles. You will work with a team of world-class engineers with diverse backgrounds such as robotics, controls, simulation, and vehicle engineering to enable our vehicle to deliver outstanding energy efficiency and range in service. Operating a fleet of robotaxis at scale requires balancing performance, cost, and energy usage at the time - in this position, you will spearhead energy management and energy-efficient architectures across the vehicle platform and robotaxi fleet. You’ll collaborate on electrical powertrains, high-voltage batteries, thermal architectures, and low-voltage systems, as well as the sophisticated compute and sensing suites required for autonomous operation. In this role, you will: Develop holistic engineering and product strategies for vehicle energy management. Develop energy budgets, energy saving features, and software controls strategies across sub-systems. Work closely with simulation engineers to develop digital vehicle models for energy consumption prediction and vehicle design optimization across drive cycles. Integrate those models into larger end to end simulations to analyze fleet wide energy performance for service operations. Advocate for energy efficiency as vehicle development progresses - you’ll need passion and backbone to deliver results and make data-driven tradeoffs on behalf of energy. Qualifications Bachelor’s degree in engineering, physics, or a related technical field 7+ years of direct experience in system design and energy management in vehicular or robotics domains Familiarity with design optimization processes, including multi-disciplinary analysis and optimization Experience working with business and product stakeholders on translating business objective into engineering requirements Bonus Qualificat

As the Manager of Model Validation & Verification (VnV) for Behavior Autonomy, you will lead an engineering and data science team responsible for evaluating, benchmarking, and validating the machine learning models and behavioral algorithms that drive our autonomous vehicle (AV) prediction and planning stacks. You will own the statistical frameworks, offline/online evaluation metrics, and validation pipelines that ensure our behavioral models operate safely, comfortably, and predictably. Operating at the intersection of Data Science, Machine Learning, and Safety Engineering, you will partner closely with Autonomy Software, Prediction, Planner, and ML Operations teams to establish data driven release criteria for our AV fleet. In this role, you will: Team Leadership & Execution: Lead, mentor, and scale a high-performing team of Data Scientists, ML Validation Engineers, and Software Engineers while driving roadmaps, sprint execution, resource allocation, and high-throughput model releases with rigorous safety guardrails. Culture of Rigor: Foster a culture of statistical excellence, healthy skepticism, proactive risk tracking, and data-driven decision-making. Validation Strategy & Methodologies: Define and execute end-to-end validation strategies across offline evaluation, open/closed-loop simulation, and shadow-mode fleet benchmarking to ensure robust behavioral model performance. Statistical uncertainties, and regressions into clear, data-driven recommendations for release gating and executive leadership. Metrics, Release Gating & Rigor: Oversee metric development and standardization with System Safety and Autonomy teams, establishing quantitative go/no-go release criteria for Behavioral Planner and Prediction ML models while fostering statistical rigor and proactive risk management. Cross-Functional & Infrastructure Partnership: Partner closely with Planner, Prediction, MLOps

We are seeking a highly skilled and experienced Staff Data Scientist to join our team and play a pivotal role in developing and deploying cutting-edge autonomous driving technologies. As a Staff Data Scientist, you will be responsible for tackling complex data challenges, driving innovation in machine learning and statistical modeling, and contributing to the advancement of our self-driving systems. You will work closely with a team of talented engineers and researchers in a fast-paced, collaborative environment. In this role, you will: Analyze large-scale datasets from various sources, such as fleet and simulation data, to extract actionable insights. Develop and evaluate novel algorithms and methodologies for data processing, feature engineering, model training, and performance optimization. Evaluate and validate model performance through rigorous testing and analysis, ensuring the safety and reliability of our systems. Communicate complex technical findings and recommendations to both technical and non-technical audiences. Mentor and provide technical guidance to junior data scientists and engineers. Qualifications Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with 8+ years of experience as a Data Scientist. Strong programming skills in Python, including experience with relevant libraries such as scikit-learn, and Pandas & SQL. Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling. Experience working with large-scale datasets and distributed computing platforms (e.g., Spark, Hadoop) with solid understanding of data processing, feature engineering, and data visualization techniques. Strong communication and presentation skills, with the ability to effectively convey technical information to diverse audiences. Bonus Qualifications Experienc

We are looking for a Senior/Staff Software Engineer to lead the development and scaling of our cloud services and APIs that handle ride hailing for Zoox’s production-grade robotaxi service. These services include dispatch, routing, payments, mobile APIs, telemetry processing, service metrics and more. In this role, you will: Design and build scalable, efficient, and robust backend systems for Zoox’s ride-hailing service Own core functionality such as payments, fleet dispatch, service management Make significant contributions to technical roadmaps, development plans and execute on them effectively. Uphold engineering excellence by demonstrating best practices in software development including design review, code review, software testing and documentation. Qualifications 8+ years of cloud software experience Experience running and optimizing production-grade systems for maximum efficiency and resilience. Extensive experience with the design, implementation and operation of backend microservices. Proficiency with Kotlin or Java, REST APIs and SQL. Experience running production services using cloud infrastructure such as Kubernetes and Docker Bonus Qualifications Experience with Spring Boot based microservice architectures, PostgreSQL, Elasticsearch Experience in transportation, robotics, logistics, or autonomous vehicles. Experience with event driven architecture and Kafka. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you nee

Zoox builds and operates a fleet of purpose-built robotaxis, and every vehicle must prove its build integrity before it can carry riders. The HWSI team builds the platform that authors, schedules, and executes Build Integrity Tests (BIT) across the manufacturing line and the fleet, and turns the results into the data that engineers and operators rely on every day. In this role, you will: Own the architecture and core of our test-orchestration platform - the distributed task scheduling, execution, and result-collection engine that runs tests across manufacturing and the fleet - and you'll personally build its most complex, reliability-critical components. Lead a small engineering team of two engineers plus 1–3 contractors: setting technical direction, reviewing code, and growing the team's impact. Make the platform resilient at scale - design for safe mid-run cancellation, no result loss under failure, and predictable behavior across hundreds of test runs as the line moves toward high production rate. Build clean APIs and frameworks that let other teams plug their own test suites into the platform without forking it, multiplying the team's reach ac