ADAS ML/Data Analytics Professional

Responsibilities :

1. Developing and maintaining data analytics, infrastructure and pipeline for ADAS related sensor data.
2. Setting up data analytics and pipelines to determine anomalies and KPI violations in the ADAS functions.
3. Ownership of tool chain and technology stack.
4. Alignment of requirements, changes, maintenance with customers and internal developers.

Must have Experience:

1. Deep Expertise in programming Python and optionally Java/C++.
2. Experience in using ML approaches such as LLMs, deep learning for data analytics as well as related implementation technologies e. g. TensorFlow, Keras, PyTorch.
3. Querry languages such as KQL, SQL.
4. Fundamental understanding and experience with data structures and algorithms.
5. Experience in working cloud infrastructure and technologies based on AWS and/or AZURE.
6. Experience with Board net technologies such as Ethernet, SomeIP, CAN will be advantageous.
7. Experience in the ADAS domain preferred.
8. Experience with DevOps.
9. Beneficial: Any experience with Bazel/CI.
10. Experience with automotive Diagnostic Log and Trace (DLT) and Automotive Diagnosis.
11. Ability to work independently and take corresponding decisions.

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