AWS MLOps

1 day ago

Cochin, Kerala, India Linnk Group Full time ₹ 6,00,000 - ₹ 18,00,000 per year

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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