Senior Machine Learning Engineer

Role Overview

We are seeking a highly experienced Senior Machine Learning Engineer with a strong engineering foundation and deep expertise in building, deploying, and scaling Machine Learning and Generative AI solutions in production environments.

The ideal candidate will have 5+ years of experience across the complete ML lifecycle, from data acquisition and model development to MLOps, deployment, monitoring, and business impact measurement. The candidate should have demonstrated success in delivering commercial AI products and building production-grade AI applications leveraging modern LLMs and Generative AI frameworks.

Key Responsibilities

Machine Learning & Data Science

• Design, develop, and deploy end-to-end ML solutions at scale.
• Build and optimize predictive models, recommendation systems, NLP solutions, and deep learning applications.
• Drive the complete data science lifecycle:
• Problem formulation
• Data exploration
• Feature engineering
• Model training
• Evaluation
• Production deployment
• Monitoring and retraining

Generative AI

• Build enterprise-grade GenAI applications using:
• OpenAI
• Azure OpenAI
• Anthropic Claude
• Llama
• Mistral
• Gemini
• Design and implement:
• RAG architectures
• Agentic AI systems
• Multi-agent frameworks
• Prompt engineering strategies
• Fine-tuning pipelines

Key Responsibilities

• Design, build, deploy, and monitor production-grade ML solutions
• Develop AI/ML applications using modern ML and GenAI frameworks
• Build and optimize end-to-end ML pipelines
• Collaborate with Product and Engineering teams to deliver business impact
• Drive best practices in MLOps, model governance, and scalability

Preferred Skills

• Python, SQL, Spark
• ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)
• LLMs, RAG, Agentic AI
• Docker, Kubernetes, Cloud Platforms (AWS/Azure/GCP)
• MLOps and model deployment