SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
inDrive is building an autonomous vehicle data platform leveraging its large-scale ride-hailing fleet operating in emerging markets. The company aims to collect AV-grade data—multi-sensor streams from real vehicles on real trips—and create datasets for autonomous vehicle development, including driving model evaluation, causal annotation, and 3D scene reconstruction for simulation.
You will lead the founding team for this AV data workstream, owning the entire pipeline from vehicle data capture through processing, annotation, and delivery. This is a zero-to-one opportunity: you will hire and build a multi-disciplinary team covering large-scale data engineering, search and serving infrastructure, ML engineering (divergence detection, edge inference, VLM-based auto-labeling), 3D reconstruction research, and data annotation operations.
Key responsibilities include:
- Own the AV data workstream end-to-end: roadmap, execution, quality, and outcomes across the full pipeline
- Build the team from scratch, set the technical bar, and own hiring and team growth
- Manage ML engineers' charter across the cluster
- Set technical direction and provide design authority for onboard capture, cloud ingestion and processing at fleet scale, semantic and causal labeling, and neural scene reconstruction
- Make key technical decisions on evidence, balancing research and delivery
- Partner with leaders across data platform, ML ops, geo/mapping, and wider AV initiatives to align roadmaps and unblock delivery
- Own external technical partnerships, including relationships with the NVIDIA AV ecosystem and prospective AV partners consuming the data
- Frame milestones as decision gates, redirect work based on evidence, and keep the team shipping measurable results on schedule
Requirements:
- 10+ years of engineering experience in applied ML, autonomous systems, or large-scale data and ML platforms
- 3+ years in the autonomous vehicle industry or closely adjacent autonomy domains (AV data, simulation, evaluation platforms, ADAS, robotics perception, HD mapping)
- 4+ years managing engineering teams, with a track record of building teams from scratch and delivering zero-to-one initiatives
- 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
- Genuine engineering leadership range: successfully led data engineering, platform, or infrastructure delivery (not only ML research); can evaluate and unblock work across disciplines
- Proven ability to take large-scale ML systems from conception to production: data pipelines, training and evaluation infrastructure, models running under real-world constraints
- Strong external presence: experience owning technical partnerships, vendor/licensing relationships, or customer-facing technical engagements at senior level
- Deep fluency in modern ML stack (PyTorch or equivalent, large-scale training and inference, Python and Linux) and cloud data platforms at multi-terabyte scale
- Bachelor's degree in Computer Science, Engineering, or related field
Nice to have:
- AV industry experience specifically in offline evaluation, data mining, annotation platforms, or simulation
- 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
