Vacancy description
RIVER MOBILITY PRIVATE LIMITED
India, Bengaluru
River Mobility - Technical Lead - Data & AI in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
About River : River is a design company building multi-utility products. Our flagship product River Indie #SUVofScooters, is designed to help you get things done. Engineered to be a dependable ally on your road to success. We're a 1000+ team headquartered in Bengaluru - backed by marquee international investors, with mobility-focused funds linked to Yamaha Motors, Al-Futtaim Automotive Group, Toyota VC, Trucks Venture Capital, Mitsui & Co. Ltd, Marubeni Ventures Inc., Lowercarbon Capital, and Maniv https://jobeax.com/link/Dzkt9bWMbGeMbC47 Responsibilities : Leadership and 0-to-1 Strategy : - Team Building : Recruit, mentor, and manage a hybrid team of data engineers, data scientists, and ML engineers from scratch.- Unified Roadmap : Define and execute a multi-year technical vision that bridges scalable data infrastructure with advanced AI capabilities.- Cross-Functional Impact : Partner with Vehicle Engineering, Software, Manufacturing, and Sales to identify high-impact AI/Data use cases (e.g., supply chain forecasting, smart scooter features).Data Engineering & Infrastructure : - IoT Telemetry Pipelines : Architect low-latency, high-throughput streaming pipelines to ingest real-time data from vehicle sensors (VCU, BMS), mobile apps, and charging infrastructure using MQTT, Apache Kafka, or AWS Kinesis.- Modern Data Stack : Design and scale a unified Lakehouse/Warehouse (e.g., Databricks, Snowflake) to handle both streaming telemetry and complex enterprise data (ERP, CRM, MES).- Data Pipelines : Build automated, resilient ETL/ELT workflows using tools like Apache Airflow, dbt, and PySpark to ensure high data quality and https://jobeax.com/link/5bJTWTcWccWa6CSt Intelligence & Machine Learning : - Predictive Modeling : Develop and deploy ML models specific to the EV ecosystem - such as predictive maintenance, Battery State of Health (SoH) degradation forecasting, and dynamic Range/State of Charge (SoC) estimation.- Rider Intelligence : Build algorithms to analyze rider behavior, detect anomalies (e.g., accident or fall detection), and personalize the app/scooter experience.- MLOps & Deployment : Establish the MLOps infrastructure (e.g., MLflow, Kubeflow) to train, deploy, monitor, and retrain models seamlessly in production - both in the cloud and on edge devices (vehicle ECUs).Ideal Candidate : - Experience : 8 - 10+ years of comprehensive experience across Data Engineering and Data Science, with at least 2 - 3 years leading technical teams or complex, multi-disciplinary data projects.- Domain Expertise : Prior experience in Automotive, EV, Telematics, or IoT is highly preferred. You must be comfortable dealing with high-frequency time-series data and geospatial (GPS) data.- Languages : Expert-level proficiency in Python and SQL.- Data Engineering : Deep practical experience with stream processing (Kafka, Spark Streaming, Flink), cloud data warehouses, and orchestration (Airflow, dbt).- AI/ML Frameworks : Strong hands-on experience with machine learning libraries (Scikit-learn, XGBoost, Pandas) and deep learning frameworks (PyTorch or TensorFlow).- MLOps : Proven track record of deploying machine learning models into live production environments and monitoring model drift.- Player-Coach Mentality : You possess the strategic vision to design enterprise architecture, but you still love writing production-grade code, debugging PySpark jobs, and tuning neural networks.- Mandatory 5 days work from office. (ref:hirist.tech)
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