The Role
Build and own large-scale data pipelines for vehicle imagery, GPS, camera, IMU, and LiDAR data. Manage cloud storage, synchronization, georeferencing, validation, monitoring, lifecycle, and cost controls. Prepare versioned training datasets for autonomous-driving models and contribute to geospatial data ingestion and publication. Optimize spatial queries across BigQuery, PostGIS, and GeoParquet while collaborating with machine learning and mapping teams.
Summary Generated by Built In
About the role
We are preparing the data foundation for our autonomous-driving work, and we are hiring the engineer who will start it. Today we collect street-level imagery and GPS tracks from vehicle cameras, including our own camera units with NVIDIA edge devices on board, and use them to update maps. Next comes a dedicated survey vehicle with a full sensor set: multi-camera, IMU, LiDAR. You will start with the imagery and map data pipelines we run today, and as the sensor platform arrives, you will build the pipelines that turn its data into training datasets for autonomous-driving models.
We are preparing the data foundation for our autonomous-driving work, and we are hiring the engineer who will start it. Today we collect street-level imagery and GPS tracks from vehicle cameras, including our own camera units with NVIDIA edge devices on board, and use them to update maps. Next comes a dedicated survey vehicle with a full sensor set: multi-camera, IMU, LiDAR. You will start with the imagery and map data pipelines we run today, and as the sensor platform arrives, you will build the pipelines that turn its data into training datasets for autonomous-driving models.
Key Responsibilities
- Build the pipelines that move multi-sensor data (multi-camera video, IMU, LiDAR, GPS) from vehicles into cloud storage, synchronize and geo-reference the streams
- Own the storage layout and lifecycle for sensor data: partitioning, hot and archival tiers, cost control as volume grows
- Build validation and monitoring on the ingest path: incomplete uploads, missing or unsynchronized streams, vehicles that stopped producing usable data
- Prepare training datasets for autonomous-driving models: select data by location, route, and conditions, version datasets, and deliver them in the formats ML teams need
- Until then: take over and develop the current imagery and GPS-track pipelines from vehicle cameras, and contribute to geodata pipelines (ingestion from company data, OpenStreetMap, Overture Maps and vendors, conflation, validation, publication)
- Work with company data in BigQuery and keep spatial queries fast on large PostGIS and GeoParquet tables
Skills, Knowledge & Expertise
- 4+ years in data engineering
- Experience with multi-sensor data from vehicles or robots: cameras, IMU or LiDAR, and keeping the streams in sync
- Experience preparing training datasets for computer vision or autonomous-driving models.
- Large volumes of binary or media data in object storage (S3 or GCS); distributed processing (Spark or equivalent)
- Hands-on experience with spatial data: PostGIS, GeoPandas/Shapely, coordinate reference systems, GPS tracks
- Strong Python and SQL; AWS or GCP, Docker, Kubernetes
Nice to have
- Sensor data formats such as ROS2 bag, MCAP or point clouds
- Parquet, Delta or Iceberg; Databricks
- Argo Workflows or Airflow
- OpenStreetMap and Overture Map
- QGIS
- BigQuery
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
- 4+ years of experience in data engineering
- Experience working with multi-sensor data from vehicles or robots, including cameras, IMU, or LiDAR, and synchronizing streams
- Experience preparing training datasets for computer vision or autonomous-driving models
- Experience handling large volumes of binary or media data in object storage such as S3 or GCS
- Experience with distributed processing such as Spark
- Hands-on experience with spatial data, including PostGIS, GeoPandas, Shapely, coordinate reference systems, and GPS tracks
- Strong Python and SQL skills
- Experience with AWS or GCP, Docker, and Kubernetes
- Experience with sensor data formats such as ROS2 bag, MCAP, or point clouds
- Experience with Parquet, Delta, Iceberg, or Databricks
- Experience with Argo Workflows or Airflow
- Experience with OpenStreetMap and Overture Maps
- Experience with QGIS
- Experience with BigQuery
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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.
