Principal Machine Learning Engineer (Autonomous Driving)

Location: Sunnyvale, California, USA. Hybrid working model with in-person collaboration in dedicated offices and remote work; the role may include hands-on work in vehicle workshops and labs.

Salary: $390K–$460K annually.

Company

hirify.global is building an AI platform for autonomous driving that enables vehicles to learn from real-world experience and adapt, generalise, and improve at scale.

What you will do

• Build and own the ingestion-time model that scores incoming driving data and routes it to hot, cold, archive, or delete storage.
• Work with training teams to define the data distributions required for each model.
• Deliver measurable storage-cost savings through practical heuristics and evolve the system toward ML-driven filtering.
• Define dataset content strategy, including the data and metadata required for efficient model training and selection.
• Partner with ingestion, annotation, retrieval, data quality, model training, autonomous-vehicle, robotics, evaluation, and storage teams to establish company-wide data policy.
• Lead and contribute hands-on with a small group of software and ML engineers to build data-provisioning and data-provenance features into Corpus.

Requirements

• Strong autonomous-vehicle or robotics experience with large-scale driving, sensor, or comparable data.
• Principal-level, hands-on machine learning engineering experience building models that score, select, or filter data.
• Experience operating at petabyte scale and working with the related engineering challenges.
• Strong Python and Spark skills, together with large-scale cloud data experience.
• Strong quantitative intuition and the ability to make practical, measurable decisions.
• Pragmatic, high-ownership approach and the ability to set direction across several teams without direct authority.

Nice to have

• Experience in data selection, retention, or filtering for model training.
• Experience with edge or vehicle-side filtering, computer vision, or high-volume IoT data.
• Experience leading small cross-functional groups.

Culture & Benefits

• Hybrid work combining in-person collaboration with focused remote work.
• Relocation support and visa sponsorship where applicable.
• Meaningful equity and annually benchmarked salaries.
• Learning and development budgets supporting training, conferences, and professional growth.
• Health and dental insurance, enhanced maternity and paternity leave, retirement or pension benefits where applicable, therapist access, wellbeing partnerships, and team socials.
• Core hours and opportunities to work hands-on in vehicle workshops and labs.

Hiring process

• Initial recruiter call lasting 30 minutes, followed by a one-hour hiring-manager introduction.
• Two hours of competency interviews covering system design and technical leadership, followed by a one-hour domain deep dive.
• One-hour final interview focused on mission and values alignment.