JOB DESCRIPTION
Department Global Data Insight and Analytics (GDI&A)
 
Position Title AI Engineer
 
Location of Position Chennai
 
GDIA Mission and ScopeThe Global Data Insights and Analytics (GDI&A) department at  Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization.
The goal of GDI&A is to drive evidence-based decision making by providing insights from data.
Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics.
We are seeking a highly technical and experienced individual to fill the role of Tech Anchor/Solution Architect within our Industrial System Analytics (ISA) team.
As a Tech Anchor, you will provide technical leadership and guidance to the development team, driving the design and implementation of cloud analytic solutions using GCP tools and techniques.
 
Key Roles and Responsibilities of Position:
- Develop and automate end-to-end LLM Pipelines to run efficiently in the GCP
environment, specifically leveraging Vertex AI for model training and deployment.
- Work with the team to develop and implement solutions using GCP tools (BigQuery, GCS, Dataflow, Dataproc, Vertex AI) and APIs/Microservices.
- Ensure adherence to security, legal, and Ford standard/policy compliance, with a focus on data privacy and model governance.
- Designing, training and fine-tuning AI models (including deep learning and LLMs) to solve specific business problems.
- Transitioning models from research environments to production, often by converting them into APIs or integrating them into existing software applications.
- Drive effective and efficient delivery from the team, focusing on speed and the automation of the machine learning lifecycle (CI/CD/CT).
- Identify risks and implement mitigation/contingency plans, specifically addressing data drift, model decay, and pipeline bottlenecks.
- Manage onboarding of new resources and mentor the team on MLOps best practices and infrastructure-as-code.
- Lead the design and architecture of complex ML systems, ensuring scalability,
reliability, and high performance for real-time and batch inference.
- Participate in code reviews and contribute to improving code quality for both machine learning models and underlying infrastructure code.
- Ensure effective usage of Rally to track MLOps-specific epics and stories, deriving meaningful insights into delivery velocity.
- Staying current with AI advancements (e.g., Generative AI, LLMs) and applying them to improve existing products.
- Ensure implementation of DevSecOps and software craftsmanship practices (CI/CD, TDD, Pair Programming) specifically tailored for ML workflows and model security.
- Govern model artifacts and features using tools like Vertex AI Model Registry 
 
JOB DESCRIPTION
Feature Store to ensure experiment reproducibility and consistency.
 
Qualifications:
- Bachelor's /Master's/ PhD in engineering, Computer Science, or in a related field
- Senior-level experience (8+ years) as a Software engineer or ML Engineer
- Deep and broad knowledge of:
o Programming Languages: Python, SQL
o ML/MLOps Frameworks: Vertex AI, MLflow, KubeFlow, Scikit-learn,
TensorFlow, PyTorch
o Back-End Technologies: Python frameworks (FastAPI, Flask)
o Cloud Technologies: GCP (Vertex AI, BigQuery, GCS, Dataflow, Dataproc, etc.)
o Deployment Practices: Docker, Kubernetes (GKE), CI/CD pipelines,
Infrastructure as Code (Terraform)
- Experience with Agile software development methodologies
- Understanding/Exposure of:
o CI, CD, and Test-Driven Development (GitHub, Terraform/Tekton, 42Crunch,
SonarQube, FOSSA, Checkmarx etc.)
o ML Lifecycle Management: Model Registry, Feature Store, and Model
Monitoring (Drift and Performance detection)