Machine Learning Engineer

About the job

Machine Learning Engineer – Generative AI / NLP / AWS Bedrock 📍 Location: Remote 💰 Experience: 4+ Years 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. Responsibilities: • 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. Experience Requirements: • 4+ years of experience in Machine Learning Engineering. • Production experience with MLflow. • Experience deploying LLMs or Generative AI systems in production.

Requirements

• NLP
• AWS
• Machine Learning
• Generative AI

Preferred Technologies

• NLP
• AWS
• Machine Learning
• Generative AI