Job Description

Tatigkeitsbereich:Forschung & Entwicklung incl. Design
Fachabteilung:Production Planning 1
Gesellschaft:Mercedes-Benz Research and Development India Private Limited
Standort:Mercedes-Benz Research and Development India Private Limited, Bangalore
Startdatum:sofort
Veroffentlichungsdatum:19.01.2026
Stellennummer:MER0003VRC
Arbeitszeit:Vollzeit
Aufgaben
About the Team


Join an elite AI group shaping the future of self-driving mobility. Our Autonomous Intelligence (AI) 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
Qualifikationen
About the Team


Join an elite AI group shaping the future of self-driving mobility. Our Autonomous Intelligence (AI) 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
Benefits
Mitarbeiterrabatte moglich
Gesundheitsmassnahmen
Mitarbeiterhandy moglich
Essenszulagen
Betriebliche Altersversorgung
Hybrides Arbeiten moglich
Mobilitatsangebote
Mitarbeiter Events
Coaching
Flexible Arbeitszeit moglich
Kinderbetreuung
Parkplatz
Kantine, Cafe
Gute Anbindung
Barrierefreiheit
Betriebsarzt
KontaktMercedes-Benz Research and Development India Private Limited
Plot No. 5-P, EPIP 1st Phase560066 BangaloreDetails zum Standort
Dipti Nayak E-Mail: dipti.nayak@mercedes-benz.com