AWS MLOps

4 weeks ago

Cochin, Kerala, India Linnk Group Full time

AWS MLOps & LLMOps Engineer – Reinforcement Learning & Cloud AI Specialist

Location: Kochi

Employment Type: Full-Time

Job Overview

We are seeking a hands-on and customer-facing AWS MLOps & LLMOps Engineer with expertise in reinforcement learning , SageMaker , Feature Store , and continuous ML lifecycle management . You'll lead the deployment and monitoring of ML and LLM models, support sales with RFPs, and take full ownership of AI projects from ideation to production. Experience with Kubernetes is a strong plus.

Key Responsibilities

  • Design and implement MLOps and LLMOps pipelines using AWS services (SageMaker Pipelines, Lambda, EKS, ECS, etc.)
  • Build and manage reinforcement learning pipelines , including simulation environments, reward modeling, and policy optimization
  • Integrate and maintain Amazon SageMaker Feature Store for real-time and batch feature ingestion
  • Enable continuous training , model monitoring , and automated deployment using CI/CD workflows
  • Collaborate with data scientists to operationalise ML and LLM models, including fine-tuning and prompt engineering
  • Develop and maintain High-Level Designs (HLD) and network architecture for scalable AI solutions
  • Engage with customers to understand requirements and propose tailored AI/ML solutions
  • Provide technical support for RFPs , including architecture design, effort estimation, and documentation
  • Ensure security, compliance, and governance across all ML/LLM workflows
  • Lead and support AI projects with full ownership from experimentation to production
  • Create architecture HLD with networking, data flow, components and integration diagram

Required Skills & Qualifications

  • 2-6 years of experience in MLOps , with hands-on exposure to LLMOps and reinforcement learning
  • Strong experience with AWS SageMaker , including Pipelines, Model Registry, and Feature Store
  • Proficiency in Python , Docker , Terraform , and CI/CD tools
  • Familiarity with RL frameworks like Ray RLlib, OpenAI Gym, or Stable Baselines
  • Experience with ML frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers
  • Solid understanding of networking , security protocols , and cloud-native architecture
  • Excellent communication and client engagement skills
  • Bachelor's or master's degree in computer science, Data Science, or related field

Preferred Qualifications

  • Good to have experience with Kubernetes (EKS preferred) for container orchestration and scalable ML deployments
  • AWS Certified Machine Learning Speciality or equivalent certifications
  • Exposure to model monitoring tools (e.g., SageMaker Model Monitor, Prometheus, Grafana)
  • Knowledge of LLM evaluation , bias detection , and hallucination mitigation
  • Familiarity with data lake architectures , feature engineering , and metadata management

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