Work Type: Direct Hire / Full-Time
Experience Required: 10 – 21 Years
Compensation: USD 150,000 – 199,000 Per Annum + Bonus up to 20%
Eligibility: Green Card Holders, US Citizens, H1B Transfer
Travel Requirement: As Required (Client Workshops & Solutioning)
Job Overview
• We are seeking a highly experienced AI Consultant with strong expertise in machine learning, deep learning, generative AI, and agentic AI, backed by robust domain knowledge in Manufacturing & Service Lifecycle Management (SLM).
• The ideal candidate is a full-stack AI engineer capable of architecting, developing, and scaling AI solutions across automotive, commercial vehicles, heavy equipment, and industrial manufacturing environments.
• This role blends hands-on technical work with consultative leadership, including pre-sales support, client advisory, PoCs, and end-to-end AI solution delivery.
Key Responsibilities
• Identify AI use cases, lead workshops, and design scalable solutions.
• Build PoCs and prototypes to validate business value.
• Develop AI pipelines for vision, NLP, and time-series.
• Build GenAI apps, agent workflows, and RAG-based knowledge systems.
• Own end-to-end delivery from data to deployment.
• Deploy AI solutions on AWS/Azure/GCP.
• Implement MLOps pipelines, CI/CD, and monitoring.
• Deploy models via Docker/Kubernetes and APIs.
• Apply AI to design, production, quality, and service operations.
• Build predictive maintenance, defect detection, and process optimization solutions.
• Lead client presentations and innovation demos.
• Mentor teams and contribute to reusable AI frameworks.
Must-Have Qualifications
• 12–15 years of experience in AI/ML, including 2+ years in Generative AI / LLMs / Agentic AI.
• Strong expertise in ML, DL, NLP, vision systems, and time-series modeling.
• Proficiency in Python and ML frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain.
• Proven cloud delivery experience on AWS / Azure / GCP.
• Hands-on experience with Docker, Kubernetes, API deployment.
• Proficiency in MLOps/LLMOps tools: MLflow, Azure ML, Vertex Pipelines, Kubeflow.
• Strong knowledge of manufacturing operations, IoT, field service, and SLM data models.
• Excellent communication & client-facing skills.
Nice-to-Have Qualifications
• Experience with Digital Twins, Predictive Maintenance, Industrial IoT.
• Knowledge of vector DBs: Pinecone, Weaviate, FAISS, Azure AI Search.
• Familiarity with PLM/ERP/SLM systems: PTC Windchill, Teamcenter, SAP S/4HANA.
• Automotive, commercial vehicle, or heavy machinery industry background.
• Cloud AI certifications (AWS ML Specialty, Azure AI Engineer, GCP ML Engineer).
