Data Scientist

About the Team

Join an elite AI group shaping the future of self-driving mobility. Our Autonomous Intelligence (AI²) team builds ML systems, perception-driven insights, predictive models, and simulation-validated algorithms that power next-generation autonomous vehicles.
We work with petabyte-scale multimodal datasets collected from global test fleets—LiDAR, Radar, Camera, CAN, HD Maps—and transform them into deployable intelligence for safer and smarter mobility.

What You’ll Do

• Design algorithms for data mining, clustering, pattern recognition, and anomaly detection in large-scale autonomous-driving datasets.
• Architect and deploy end-to-end ML pipelines for perception analytics, driving behavior modeling, risk assessment, and ADAS validation.
• Evaluate the performance of ML/DL algorithms (e.g., object detection, tracking, sensor fusion, trajectory prediction) using state-of-the-art metrics.
• Build and optimize feature stores, real-time data processing pipelines, and large-scale distributed computing systems.
• Work with global teams to implement technical solutions using Azure, Databricks, Kubernetes, and Spark ecosystems.
• Develop advanced visualizations/dashboards for fleet insights, behavior analytics, and safety validation.
• Collaborate with perception, localization, simulation, and cloud teams to integrate ML models into production AV systems.
• Drive research on next-generation approaches using transformer models, foundation models for AV, and generative simulation.

Required Technical Skills

Programming & Data Engineering

• Expert in Python, PySpark, MLlib, SQL; strong in Scala (nice to have)
• Strong experience with distributed data pipelines and big-data architecture
• Hands-on with Delta Lake, Databricks, MLFlow, Feature Store

Machine Learning / Deep Learning

• Solid understanding of:
  • CNNs, RNNs, LSTM/GRU
  • Transformers (ViT, DETR, BEVFormer, BEVFusion)
  • Self-supervised learning (MAE, etc.)
  • Reinforcement learning (for behavior modeling)
  • Probabilistic modeling, Bayesian ML
• Experience evaluating ADAS/AV algorithms for:
  • Object detection & tracking
  • Lane & road feature extraction
  • Trajectory prediction
  • Driving style classification

Cloud / DevOps

• Strong experience building CI/CD workflows with:
  • Kubernetes, Docker, Helm
  • Azure Cloud (ADF, HDInsight, AKS, Azure Storage, Databricks)
• Nice to have:
  • AWS or GCP exposure
  • Kafka / EventHub stream processing
  • Elasticsearch + Kibana dashboards

Autonomous Driving Domain Skills

• Experience with:
  • Sensor data: Camera, LiDAR, Radar, CAN
  • Simulation tools: CARLA, NVIDIA DRIVE Sim
  • HD maps / map-matching
  • Annotation/labeling pipelines
  • Safety metrics for AV validation (RSS, TTC, decel models)

Education

• Bachelor’s/Master’s in Computer Science, Electrical/EC Engineering, Robotics, or similar
• Candidates with research publications/patents in AV/ADAS/ML get high preference

Why Join

• Solve meaningful, globally impactful problems
• Work with petabyte-scale multi-sensor data
• Build intelligence for the next era of self-driving vehicles
• Collaborate with global experts in AI, robotics, software, cloud, and automotive

About the Team

Join an elite AI group shaping the future of self-driving mobility. Our Autonomous Intelligence (AI²) team builds ML systems, perception-driven insights, predictive models, and simulation-validated algorithms that power next-generation autonomous vehicles.
We work with petabyte-scale multimodal datasets collected from global test fleets—LiDAR, Radar, Camera, CAN, HD Maps—and transform them into deployable intelligence for safer and smarter mobility.

What You’ll Do

• Design algorithms for data mining, clustering, pattern recognition, and anomaly detection in large-scale autonomous-driving datasets.
• Architect and deploy end-to-end ML pipelines for perception analytics, driving behavior modeling, risk assessment, and ADAS validation.
• Evaluate the performance of ML/DL algorithms (e.g., object detection, tracking, sensor fusion, trajectory prediction) using state-of-the-art metrics.
• Build and optimize feature stores, real-time data processing pipelines, and large-scale distributed computing systems.
• Work with global teams to implement technical solutions using Azure, Databricks, Kubernetes, and Spark ecosystems.
• Develop advanced visualizations/dashboards for fleet insights, behavior analytics, and safety validation.
• Collaborate with perception, localization, simulation, and cloud teams to integrate ML models into production AV systems.
• Drive research on next-generation approaches using transformer models, foundation models for AV, and generative simulation.

Required Technical Skills

Programming & Data Engineering

• Expert in Python, PySpark, MLlib, SQL; strong in Scala (nice to have)
• Strong experience with distributed data pipelines and big-data architecture
• Hands-on with Delta Lake, Databricks, MLFlow, Feature Store

Machine Learning / Deep Learning

• Solid understanding of:
  • CNNs, RNNs, LSTM/GRU
  • Transformers (ViT, DETR, BEVFormer, BEVFusion)
  • Self-supervised learning (MAE, etc.)
  • Reinforcement learning (for behavior modeling)
  • Probabilistic modeling, Bayesian ML
• Experience evaluating ADAS/AV algorithms for:
  • Object detection & tracking
  • Lane & road feature extraction
  • Trajectory prediction
  • Driving style classification

Cloud / DevOps

• Strong experience building CI/CD workflows with:
  • Kubernetes, Docker, Helm
  • Azure Cloud (ADF, HDInsight, AKS, Azure Storage, Databricks)
• Nice to have:
  • AWS or GCP exposure
  • Kafka / EventHub stream processing
  • Elasticsearch + Kibana dashboards

Autonomous Driving Domain Skills

• Experience with:
  • Sensor data: Camera, LiDAR, Radar, CAN
  • Simulation tools: CARLA, NVIDIA DRIVE Sim
  • HD maps / map-matching
  • Annotation/labeling pipelines
  • Safety metrics for AV validation (RSS, TTC, decel models)

Education

• Bachelor’s/Master’s in Computer Science, Electrical/EC Engineering, Robotics, or similar
• Candidates with research publications/patents in AV/ADAS/ML get high preference

Why Join

• Solve meaningful, globally impactful problems
• Work with petabyte-scale multi-sensor data
• Build intelligence for the next era of self-driving vehicles
• Collaborate with global experts in AI, robotics, software, cloud, and automotive