The Role
Founding leader for inDrive’s autonomous vehicle data workstream. Owns the roadmap and end-to-end delivery of vehicle data capture, cloud processing, annotation, evaluation, and AV-grade datasets. Builds and leads a multidisciplinary engineering team, sets technical direction across ML, data platforms, 3D reconstruction, and inference, manages external partnerships, and balances open research with production delivery.
Summary Generated by Built In
Autonomous vehicles are coming to the markets in which inDrive serves, but the AV industry has a blind spot: it has almost no data from the cities where we operate. inDrive runs one of the world's largest ride-hailing fleets, concentrated in exactly the emerging markets global AV players have yet to reach. We are building the team that turns that fleet into an AV grade data platform: large scale multi sensor collection from real vehicles on real trips, evaluation of driving models against human drivers, automated and human in the loop causal annotation, and camera first 3D scene reconstruction for simulation.
We are hiring the founding leader of this workstream. This is a rare true zero to one: you will hire the team, stand up the vehicles and the data platform, set the technical bar, and own delivery end to end.
Key Responsibilities
- Own the AV data workstream end to end. Roadmap, execution, quality, and outcomes, from vehicle data capture through processing, annotation, and delivery of AV-grade datasets
- Build the team from zero. Hire and lead a multi disciplinary team covering large scale data engineering, search and serving, ML engineering across divergence detection, edge inference, and VLM based auto labeling, 3D reconstruction research, and data annotation operations. Own the hiring bar and the team's growth
- Management: Manage ML engineers' charter across the cluster
- Set technical direction across disciplines. Provide design authority for the full pipeline, including onboard capture, cloud ingestion and processing at fleet scale, semantic and causal labeling, and neural scene reconstruction, and make the key technical decisions on evidence
- Partner with leaders across the organization. Work closely with the leaders of data platform, ML ops, geo and mapping, and inDrive's wider autonomous vehicle initiatives to align roadmaps, share infrastructure, and unblock delivery
- Own external partnerships. Drive the technical relationships this work depends on, including the NVIDIA AV ecosystem and prospective AV partners consuming our data
- Balance research and delivery. Several of the core questions here are open research. You frame milestones as decision gates, redirect work based on evidence, and keep the team shipping measurable results on a schedule
Skills, Knowledge and Expertise
- 10+ years of engineering experience in applied ML, autonomous systems, or large-scale data and ML platforms, including 3+ years in the autonomous vehicle industry or closely adjacent autonomy domains (AV data, simulation, or evaluation platforms, ADAS, robotics perception, HD mapping), and 4+ years managing engineering teams, with a track record of building teams from scratch and delivering from zero to one
- Strong command of the modern AV and foundation model landscape: vision-language models, multi-modal perception, 3D reconstruction and neural rendering, and the NVIDIA AV ecosystem. Deep enough to set direction, review designs, and make evidence-based technical calls
- Genuine engineering leadership range: you have successfully led data engineering, platform, or infrastructure delivery, not only ML research, and can evaluate and unblock work across those disciplines
- Proven ability to take large-scale ML systems from conception to production: data pipelines, training and evaluation infrastructure, and models running under real-world constraints
- Strong external presence: experience owning technical partnerships, vendor and licensing relationships, or customer-facing technical engagements at a senior level
- Deep fluency in the modern ML stack (PyTorch or equivalent, large-scale training and inference, Python and Linux) and in cloud data platforms at multi-terabyte scale
- Bachelor's degree in Computer Science, Engineering, or a related field
Nice to have:
- AV industry experience specifically in offline evaluation, data mining, annotation platforms, or simulation, as distinct from on-vehicle stack development
- Advanced degree (MS or PhD) in ML, robotics, or computer vision
- Experience operating in emerging markets, and comfort building where the playbook does not exist yet
Why join us
- Help us challenge injustice by creating fair choices for millions of people across 47 countries
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects
- Work alongside people who take initiative, speak openly, and challenge themselves to grow
- Improve your language skills through co-financed courses and internal speaking clubs
Final benefits may vary depending on the location.
About
inDrive is a global tech company on a mission to challenge injustice through fair choices. We started in 2012 in the coldest city on Earth, when a group of friends created a way for people to agree on fair ride prices. That idea grew into one of the world’s top ride-hailing apps, now with 400M installs across 47 countries.Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. We are committed to having a positive impact on people’s lives both through our core business, which supports local communities via a fair pricing model; and through the work of our impact programs. Ready to ignite your inner drive?
Skills Required
- 10+ years of engineering experience in applied machine learning, autonomous systems, or large-scale data and machine learning platforms
- 3+ years of experience in the autonomous vehicle industry or closely adjacent autonomy domains
- 4+ years managing engineering teams
- Track record of building teams from scratch and delivering zero-to-one initiatives
- Strong knowledge of vision-language models, multimodal perception, 3D reconstruction, neural rendering, and the NVIDIA AV ecosystem
- Experience leading data engineering, platform, or infrastructure delivery
- Experience taking large-scale machine learning systems from conception to production
- Experience with data pipelines, training and evaluation infrastructure, and models operating under real-world constraints
- Experience owning senior-level technical partnerships, vendor or licensing relationships, or customer-facing technical engagements
- Fluency in PyTorch or equivalent, large-scale training and inference, Python, Linux, and multi-terabyte cloud data platforms
- Bachelor's degree in Computer Science, Engineering, or a related field
- AV experience in offline evaluation, data mining, annotation platforms, or simulation
- Advanced degree in machine learning, robotics, or computer vision
- Experience operating in emerging markets
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The Company
What We Do
inDrive is a global IT and transportation platform inDrive is one of the world’s fastest growing online ride-hailing services. Its services are available in over 749 cities in 46 countries throughout the world. The Company’s app has been downloaded over 150 million times. inDrive offers other services, including intercity transportation, freight and cargo services, as well as delivery services in different markets of operations. inDrive is based in Mountain View, California, and operates regional hubs in the Americas, Asia, the Middle East, Africa and the countries of the CIS, and employs over 2,000 people. In early 2021, inDrive achieved unicorn status after closing a $140m investment round with Insight Partners, General Catalyst, and Bond Capital, which valued the company at $1.23 billion.
