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AI Transformation Consultant – Engineering & Aftersales
Job in
Oakland, Alameda County, California, 94616, USA
Listed on 2026-01-01
Listing for:
Mogi I/O : OTT/Podcast/Short Video Apps for you
Full Time
position Listed on 2026-01-01
Job specializations:
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
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)
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.
- 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:
Tensor Flow, PyTorch, Scikit-learn, Hugging Face, Lang Chain.
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.
- 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/4
HANA. - Automotive, commercial vehicle, or heavy machinery industry background.
- Cloud AI certifications (AWS ML Specialty, Azure AI Engineer, GCP ML Engineer).
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