Top Tech Jobs & Startup Jobs

Develop and operate internal Kubernetes-based platforms, infrastructure automation, workflow systems, observability tooling, API gateways, and messaging platforms. Support data, simulation, ML, CI/CD, and LLM workflows; improve reliability, cost efficiency, and platform visibility. Participate in on-call rotations, incident response, documentation, and internal user enablement while receiving mentorship and contributing production code.

Develop and maintain onboard infrastructure for autonomous driving systems, including sensor drivers, health management, middleware, diagnostics, logging, recovery, and real-time data handling. Optimize autonomous driving software for embedded systems and onboard computing platforms, focusing on low latency, deterministic performance, computational efficiency, reliability, and system integration.

Develop and improve autonomous truck planning and control algorithms using C++ and Python. Investigate driving issues through simulation, vehicle data, logs, and code analysis; design rigorous experiments; analyze failures and regressions; document reproducible results; and collaborate with validation and simulation engineers on testing and autonomy-stack integration.

Manage enterprise IT infrastructure across offices, data centers, endpoints, and SaaS environments. Lead IAM, system reliability, patching, MDM, virtualization, storage, ITSM workflows, and automation initiatives. Lead and mentor a small IT team while remaining hands-on with escalations, projects, technical direction, workload planning, and on-call operations. Support security compliance, audit readiness, and autonomous trucking operations.

Supports corporate IT operations through user onboarding and offboarding, asset inventory, laptop deployment, help desk support, monitoring and alert triage, patching, software deployment, documentation, and office IT logistics. The intern assists with hardware, software, access, conference room AV, desk setups, and equipment moves while gaining exposure to enterprise tooling, networking, identity management, and infrastructure automation.

Build and improve AI agents that automate engineering, fleet operations, and business workflows. Responsibilities include integrating LLMs with internal systems, implementing planning and tool-using agent workflows, developing backend services and APIs, evaluating models and frameworks, and contributing to internal AI platforms. The role requires strong programming fundamentals, Python or comparable language skills, and familiarity with machine learning or LLMs. Preferred experience includes agent frameworks, RAG, vector databases, cloud platforms, and containerization.

Owns core platforms that deliver autonomous driving software from development through vehicle deployment. Responsibilities include C++ build and packaging systems, CI/CD, Docker and Kubernetes infrastructure, cloud and edge services, APIs, event-driven architecture, identity and access control, PKI, mTLS, secrets management, and fleet operations. The role also involves code review, architectural design, infrastructure on-call, mentoring, and cross-team technical leadership.

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

Lead functional and system safety engineering for a Level 4 autonomous trucking platform. Responsibilities include hazard analysis, safety requirements, safety cases, risk assessments, FMEA, fault-tree and STPA analyses, ODD evaluation, verification and validation strategy, supplier coordination, launch readiness, incident analysis, and safety governance. The role partners across autonomy, hardware, software, vehicle integration, operations, fleet, and testing teams to ensure safety risks are identified, mitigated, traceable, and supported by evidence for deployment decisions.

Perform state-of-the-art prototyping and benchmarking of multi-modal perception, mapping, and prediction models. Own a focused research project from data analysis through model verification. Train, tune, and optimize deep learning models on large-scale compute and truck datasets under senior mentorship.