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Protocol Intelligence
Data-driven signals on your job's competitivenessKnown employer, metro location, and sought-after ML/AI senior role produce moderate candidate competition.
Automotive edge deployment, embedded C++ integrations, and safety standards demand highly specific domain backgrounds.
Explicit 8+ years, automotive edge specialization, and mandatory ML/dev tooling make shortlisting highly strict.
Job Description
Structured overview of role & requirementsAbout This Role
Develop and deploy AI/ML models including Small Language Models (SLMs), Visual Language/Audio (VLA/VLM) models for in-vehicle conversational AI and multi-modal perception within edge and cloud environments.
Build AI orchestration systems handling intent/tool routing, policy engines, scheduling, and cross-domain context management across cockpit, ADAS, and connected vehicle experiences.
Design and implement ML pipelines and MLOps workflows ensuring compliance with safety, cybersecurity, and automotive standards; collaborate with embedded software, cloud/data teams, and system integration groups.
Minimum Requirements
8+ years of AI/ML engineering experience focused on deep learning, NLP, and computer vision.
Strong programming skills in Python (mandatory) and preferably C++.
Experience with AI model deployment on embedded/edge platforms and cloud environments (Azure, AWS, GCP).
Work Experience Required: Minimum 8 years in AI/ML roles as per JD.
Ideal Candidate Profile
Experience in automotive domain technologies such as ADAS, cockpit systems, and vehicle connectivity.
Familiarity with agentic AI, orchestration frameworks (e.g., LangChain), and multi-modal AI model deployment.
Skilled in end-to-end AI system development including MLOps, model lifecycle management, and optimization on edge devices using C++ APIs or NNAPI.