Core AI/ML Development

- Partner with business, product, and engineering teams to define problem statements, evaluate feasibility, and design AI/ML-driven solutions that deliver measurable business value
- Lead and execute end-to-end AI/ML projects from data exploration and model development to validation, deployment, and monitoring in production
- Independently design and implement scalable machine learning solutions and data systems, ensuring end-to-end workflows, large-scale analytics, and reliability

Generative AI LLM Implementation

- Design and implement RAG (Retrieval Augmented Generation) systems for enterprise knowledge management
- Develop guardrails and safety measures for GenAI applications in production
- Implement cost optimization strategies for LLM inference at scale
- Create synthetic data generation pipelines for model training and testing
- Build and optimize prompt engineering strategies and fine-tuning pipelines

Traditional ML Excellence

- Drive solution architecture using techniques in data engineering, programming, machine learning, NLP, and computer vision
- Implement and refine feature engineering, monitoring, ML pipelines, deploy models in production
- Build real-time inference APIs with sub-second latency requirements
- Develop forecasting models for demand prediction and supply chain optimization




- Create recommendation systems for route optimization and customer solutions

MLOps Production Engineering

- Champion the scalability, reproducibility, and sustainability of AI solutions by establishing best practices in model development, CI/CD, and performance tracking
- Ensure readiness for production releases, focusing on testing, monitoring, observability, and maintaining scalability
- Implement comprehensive model versioning, registry, and rollback strategies
- Build automated retraining pipelines and drift detection systems

Leadership Collaboration

- Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews
- Translate technical outputs into actionable insights for business stakeholders through storytelling and data visualizations
- Drive cross-team and cross-discipline initiatives to optimize workflows and enhance collaboration
- Identify and evangelize the adoption of emerging tools, technologies, and methodologies across teams

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior AIML Engineer (Bengaluru)
🏢 APM Terminals
📍 Bengaluru