Job Title

Machine Learning Engineer – Generative AI / NLP / AWS Bedrock Location:Remote Budget:Up to ₹1 LPM Working Hours:Minimum overlap with8:00 AM – 4:00 PM EST Experience:4+ Years About the Role We are looking for aMachine Learning Engineer with strong expertise in Generative AI, NLP, and MLOpsto help build and scale amulti-model AI platform running on AWS infrastructure . The ideal candidate will work onLLM 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 scalableAI-powered applications using AWS Bedrock and transformer-based models . This role is ideal for someone passionate aboutLarge Language Models, generative AI systems, and production-grade ML pipelines . Key Responsibilities Design and developNLP pipelinesfor: Text processing Document understanding Semantic search Text summarization Build and optimizemachine learning training pipelinesfor NLP and Generative AI models. Developsynthetic data generation and data augmentation workflowsto enhance training datasets. ManageML experiment tracking, model registry, and lifecycle management using MLflow . Deploy and manageGPU-based ML training workloads on Kubernetes / AWS EKS . Work withLarge Language Models (LLMs)and task-specific ML models. Build and integrateGenerative AI workflows using AWS Bedrockand other LLM platforms. Contribute tomodel serving infrastructure and inference APIsfor multi-model AI platforms. Ensurereproducibility, monitoring, and observabilityof ML experiments and production models. Required Skills Machine Learning & NLP Strong hands-on experience inNatural Language Processing (NLP) Experience withTransformer-based models and Large Language Models (LLMs) Experience with: Text processing Document analysis Embeddings Semantic search Summarization Experience working withGenerative AI workflows Programming Strong proficiency inPython Experience with ML frameworks: PyTorch TensorFlow Hugging Face Transformers MLOps Hands-on experience withMLflow , including: Experiment tracking Model registry Model lifecycle management Infrastructure Experience withKubernetes (preferably AWS EKS) Experience runningGPU-based ML workloads Familiarity withDocker containers Data & Training Pipelines Experience designingML training pipelines Experience withdataset preparation and data versioning Understanding ofexperiment reproducibility Experience withsynthetic data generation or data augmentation(preferred) Cloud Platforms Experience working withAWS cloud services Familiarity with: Amazon S3 AWS Lambda API-based ML services Experience withAWS Bedrockfor Generative AI or LLM applications Nice to Have Experience withLLM platforms such as AWS Bedrock or OpenAI APIs Experience withdistributed training or Kubernetes Jobs Experience buildingmodel serving APIs using FastAPI or TorchServe Experience designingscalable 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 withMLflow Experience deployingLLMs or Generative AI systems in production How to Apply Interested candidates can share their CV at Subject Line:Machine Learning Engineer – Generative AI