Data Platform Engineer (AI)

Location: London, United Kingdom. Hybrid working model with in-person collaboration in the London office and remote work.

Company

hirify.global builds an AI platform for autonomous driving, using embodied intelligence and real-world learning to support scalable vehicle autonomy.

What you will do

• Design, build, and evolve scalable data pipeline and orchestration infrastructure for autonomous driving data.
• Revamp the existing Harness system and develop a new DAG-based workflow platform.
• Build tooling and shared libraries for data ingestion, processing, inference, and evaluation workflows.
• Improve the efficient execution of hundreds of parallel pipeline steps through resource prioritisation and conflict prevention.
• Support batch inference, performance optimisation, and cost-effective evaluation workflows.
• Improve platform reliability, usability, quality, and incident response in line with business-defined SLOs.

Requirements

• Strong software engineering fundamentals and experience building and maintaining production-grade systems.
• Solid Python programming skills and experience with distributed systems, large data volumes, or high-throughput processing.
• Knowledge of unit testing, integration testing, test-driven development, and data-driven development.
• Familiarity with distributed event streaming platforms such as Apache Kafka.
• Understanding of database principles and consistency models, including eventual and strong consistency.
• Experience with databases or data warehouses such as Postgres, ClickHouse, or column-oriented databases, plus the ability to work with platform users and partner teams.

Nice to have

• Experience in data engineering, data platforms, workflow orchestration, or pipeline infrastructure.
• Experience with machine learning infrastructure, inference systems, or ML performance optimisation.
• Exposure to large-scale batch processing, compute scheduling, or resource prioritisation.
• Experience with Ray, Flyte, Spark, shared libraries, developer tooling, or internal platforms.

Culture & Benefits

• Hybrid working with core hours and access to vehicle workshops and labs.
• Relocation support and visa sponsorship where applicable.
• Market-benchmarked salaries and meaningful equity.
• Learning and development budgets for training, conferences, and professional growth.
• Health and dental insurance, enhanced parental leave, retirement or pension benefits where applicable, therapy access, wellbeing partnerships, and team socials.

Hiring process

• Initial recruiter call followed by a hiring manager meeting and domain interview.
• Deep-dive technical interviews covering programming, systems, and domain-specific topics.
• Final interview focused on mission and values alignment.