Graduate In Training Program (GIT), AI Development (Linux)
Core
Design and prototype machine learning models, adapt large language models for automotive domains, and develop end-to-end pipelines combining ASR, LLM inference, and TTS for automotive features.
Role type
Graduate Machine Learning Engineer (Automotive)
Builds
Proof-of-concept/research projects integrating ML models into automotive applications
Domain
Automotive software development, Machine Learning, Embedded Systems
Deliverable
production ML models | product features
Required skills
Machine learning algorithms, Python, ML frameworks (TensorFlow/Pytorch), ASR toolkits, TTS frameworks, Linux command-line, C++ fundamentals, Build systems (CMake/Make), Automotive communication protocols (SOME/IP, MQTT, protobuf)
Preferred skills
Network packet capture tools (tcpdump, Wireshark), RTMaps
Technologies
GPT, LLaMA, OpenAI Whisper, Vosk, Kaldi, CMake, Make, Git, SOME/IP, MQTT, protobuf
Responsibilities
Design and prototype machine learning models tailored for automotive features, Adapt and fine-tune pre-trained large language models for specific automotive domains, Develop end-to-end pipelines combining ASR, LLM inference, and TTS, Benchmark various model architectures and optimize parameters for performance, Write, test, and optimize high-performance C++ code for Linux-based systems, Work with middleware teams to define, implement, and integrate services over the automotive Ethernet stack
Seniority
Graduate (2024-2025)
