Top Tech Jobs & Startup Jobs

Build AI/ML-powered consumer products and scalable distributed systems for Uber’s grocery and food experiences. Drive projects from scoping and experimentation through deployment and maintenance, while designing and optimizing systems and algorithms at scale. Collaborate with product, operations, and data science stakeholders to deliver measurable customer and business outcomes.

Develop and optimize machine learning models and scalable software systems for Uber’s delivery marketplace. Build data pipelines and foundational infrastructure, manage the full software lifecycle, debug production issues, improve reliability and performance, and collaborate with Product, Data Science, and Operations. The role also involves code reviews, testing, monitoring, technical-debt reduction, and designing maintainable ML solutions for high-load distributed systems.

Design, develop, and maintain backend software, distributed systems, infrastructure, and data pipelines at massive scale. Own features through the full software lifecycle, including design, testing, production debugging, incident management, and performance improvement. Collaborate with Product, Data Science, and Operations, translate ambiguous requirements into system designs, conduct code reviews, and improve reliability while managing technical debt and dependencies.

Build and scale backend marketplace systems, infrastructure, and data pipelines for high-volume global platforms. Responsibilities include designing moderately complex features, owning the software lifecycle, debugging production issues, managing incidents, collaborating cross-functionally, conducting code reviews, writing tests, improving performance, and ensuring reliability. The role requires backend, distributed systems, or data engineering experience and may involve Spark, Flink, or Kafka.

Build and evolve Uber One membership platforms serving millions of global users across UberEats and UberX. Design highly available, scalable systems; lead microservices and API architecture; resolve complex technical challenges; drive platform strategy, testing, monitoring, and incident management standards; and lead technical projects from inception through global deployment while collaborating across engineering, product, data science, design, and partner teams.

Leads technical talent sourcing strategy for engineering teams across North America. Responsibilities include market mapping, targeted sourcing, data-driven hiring insights, stakeholder influence, candidate advocacy, pipeline diversity, assessment-process improvements, and delivering a high-quality candidate experience in a fast-paced environment.

Architect and build scalable engineering systems while developing and optimizing machine learning models for Uber’s delivery marketplace. Lead organization-wide frameworks and engineering projects, solve low-latency and high-correctness problems, oversee incident management, and collaborate with Product, Science, and Operations. Mentor engineers, drive technical roadmaps, improve developer velocity, and support reliable systems at global scale.

Leads strategy and planning for Uber’s Autonomous business, developing AV strategy, competitive positioning, data-driven decision frameworks, reporting governance, and planning processes. Partners with senior leaders across operations, business development, product, engineering, policy, finance, and investor relations. Manages an analytical strategy team and drives informed decisions, organizational alignment, and value creation for the autonomous business.

Leads product operations for Identity by designing go-to-market plans, operating models, rollout and testing strategies, and scalable global processes. Coordinates cross-functional teams across product, engineering, legal, tax, and support; surfaces customer and business insights; tracks post-launch metrics; and drives continuous product improvement. Requires analytical decision-making, SQL proficiency, global project management, and stakeholder leadership.

Develop scalable ML infrastructure for autonomous vehicle use cases within Uber AV Labs. Responsibilities include designing multi-region, multi-cloud platforms; customizing Uber’s ML platform; aligning infrastructure and AV teams; executing technical projects from conception through production; and optimizing GPU efficiency. The role requires expertise in CUDA, TensorRT, Kubernetes, Flyte or Airflow, and Ray, along with at least six years of experience and a computer science degree.