Senior Machine Learning Engineer

Machine Learning Engineer – Generative AI / NLP / AWS Bedrock

Location: Remote

Budget: Up to ₹1 LPM

Working Hours: Minimum overlap with 8:00 AM – 4:00 PM EST

Experience: 4+ Years

About the Role

We are looking for a Machine Learning Engineer with strong expertise in Generative AI, NLP, and MLOps to help build and scale a multi-model AI platform running on AWS infrastructure .

The ideal candidate will work on LLM pipelines, NLP systems, ML training infrastructure, and MLOps workflows deployed on Kubernetes (AWS EKS) . You will collaborate closely with cloud engineers and platform teams to develop scalable AI-powered applications using AWS Bedrock and transformer-based models .

This role is ideal for someone passionate about Large Language Models, generative AI systems, and production-grade ML pipelines .

Key Responsibilities

• Design and develop NLP pipelines for: • Text processing • Document understanding • Semantic search • Text summarization • Build and optimize machine learning training pipelines for NLP and Generative AI models. • Develop synthetic data generation and data augmentation workflows to enhance training datasets. • Manage ML experiment tracking, model registry, and lifecycle management using MLflow . • Deploy and manage GPU-based ML training workloads on Kubernetes / AWS EKS . • Work with Large Language Models (LLMs) and task-specific ML models. • Build and integrate Generative AI workflows using AWS Bedrock and other LLM platforms. • Contribute to model serving infrastructure and inference APIs for multi-model AI platforms. • Ensure reproducibility, monitoring, and observability of ML experiments and production models. Required Skills Machine Learning & NLP

• Strong hands-on experience in Natural Language Processing (NLP) • Experience with Transformer-based models and Large Language Models (LLMs) • Experience with: • Text processing • Document analysis • Embeddings • Semantic search • Summarization • Experience working with Generative AI workflows Programming • Strong proficiency in Python • Experience with ML frameworks: • PyTorch • TensorFlow • Hugging Face Transformers MLOps • Hands-on experience with MLflow , including: • Experiment tracking • Model registry • Model lifecycle management Infrastructure • Experience with Kubernetes (preferably AWS EKS) • Experience running GPU-based ML workloads • Familiarity with Docker containers Data & Training Pipelines • Experience designing ML training pipelines • Experience with dataset preparation and data versioning • Understanding of experiment reproducibility • Experience with synthetic data generation or data augmentation (preferred) Cloud Platforms • Experience working with AWS cloud services • Familiarity with: • Amazon S3 • AWS Lambda • API-based ML services • Experience with AWS Bedrock for Generative AI or LLM applications Nice to Have • Experience with LLM platforms such as AWS Bedrock or OpenAI APIs • Experience with distributed training or Kubernetes Jobs • Experience building model serving APIs using FastAPI or TorchServe • Experience designing scalable AI platforms or multi-model ML systems Experience Requirements • 4+ years of experience in Machine Learning Engineering • 2+ years of hands-on NLP development • Production experience with MLflow • Experience deploying LLMs or Generative AI systems in production How to Apply Interested candidates can share their CV at

Subject Line: Machine Learning Engineer – Generative AI