Principal Engineer (AI Platform)

Location: Sunnyvale, California, USA; hybrid working model with in-person collaboration in the office and remote work.

Company

hirify.global builds an AI platform for autonomous driving, using embodied AI and real-world learning to develop adaptable driving intelligence for vehicles and OEM partners.

What you will do

• Own the end-to-end architecture of the Model Development Platform and define standards for reliability, observability, scalability, performance, latency, and availability.
• Unify front-end applications, distributed training, Spark data pipelines, and optimisation-based experiment scheduling.
• Lead architectural reviews and solve complex technical problems across web applications, distributed compute, ML Ops, data pipelines, and optimisation algorithms.
• Build systems for testing models in simulation and on the road, balancing hardware, safety, and research priorities.
• Architect pipelines that ingest, transform, and enrich petabytes of fleet sensor data and improve compute efficiency across GPU, CPU, cloud, and edge infrastructure.
• Partner with Product, Research, and Operations on the technical vision, roadmap, and platform capabilities that accelerate model development and fleet learning.

Requirements

• 10+ years of experience designing and building large-scale distributed systems, ML/AI infrastructure, full-stack web applications, or developer platforms.
• At least 3 years of experience as a staff- or principal-level engineer.
• Experience designing systems across web platforms, ML pipelines, and large-scale compute orchestration, including technologies such as Spark, Ray, Kubernetes, Airflow, or MLflow.
• Deep knowledge of distributed computing, workflow orchestration, data modelling, and API design, with the ability to write and review production-quality code.
• Experience defining SLAs/SLOs and building observable, self-healing systems with four-nines availability or better.
• Strong cross-functional communication, technical leadership, and mentoring experience.

Nice to have

• Experience applying linear programming, graph algorithms, or other mathematical optimisation techniques to operational or scheduling problems.
• Experience with end-to-end model lifecycle tooling, model artifact tracking, and evaluation workflows.
• Experience in autonomous systems, robotics, or other safety-critical domains.
• Experience with React, Flask, FastAPI, and integration between modern web frameworks and backend systems.
• Knowledge of data privacy, compliance, and secure handling of large-scale sensor data.

Culture & Benefits

• Hybrid work with dedicated offices and focused remote working time.
• Hands-on work in vehicle workshops and labs.
• Relocation support and visa sponsorship where applicable.
• Market-benchmarked salaries, equity, health and dental insurance, enhanced parental leave, retirement or pension benefits, and wellbeing support.
• Learning and development budgets for training, conferences, and professional growth.

Hiring process

• Recruiter screen followed by a hiring manager meeting.
• Deep-dive technical interviews covering programming, system design, and domain-specific topics, lasting approximately four hours in total.
• Final interview focused on mission and values alignment.