Senior AIML Engineer

APM Terminals

10 - 15 years

12 - 17 Lacs

pune

Posted:23 hours ago| Platform:

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Skills Required

supply chain computer science solution architecture machine learning open source analytics monitoring sql python logistics

Work Mode

Work from Office

Job Type

Full Time

Job Description

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

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