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MLOps / AI Engineer

Tata Consultancy Services -
Sydney NSW

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Job Details

Qualifications

CI/CD
Azure
Management
Law
Git
Google Cloud Platform
Master's degree
AWS
Docker
Machine learning
ITIL
Terrafrom
AI
High availability

Full Job Description

Job Description:

Role Overview

The MLOps / AI Engineer is responsible for designing, building, deploying, and operating production-grade machine learning and AI systems at enterprise scale. This role bridges data science, software engineering, and platform engineering to ensure AI models and applications are reliable, secure, observable, and governed throughout their lifecycle.

Key Responsibilities – MLOps & AI Platform Engineering

Design, build, and maintain end-to-end MLOps pipelines covering model development, training, validation, deployment, monitoring, retraining, and retirement.
Develop and operate scalable AI/ML platforms across development, test, and production environments.
Operationalise machine learning and LLM-based solutions with strong reliability, performance, and governance controls.
Support batch and real-time inference workloads.

Software Engineering & Automation

Develop production-quality services and automation using Python and modern software engineering practices.
Build and manage CI/CD pipelines using Git-based workflows.
Implement Infrastructure as Code (IaC) using Terraform, ARM, CloudFormation, or Bicep.

Containerisation & Cloud Deployment

Deploy AI workloads using Docker and Kubernetes.
Design cloud-native architectures on Azure, AWS, or GCP.
Implement blue/green, canary, and progressive deployment strategies.

LLMs & Generative AI

Implement LLM application patterns including prompt orchestration, RAG, embeddings, and vector databases.
Integrate with LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or AWS Bedrock.
Work with agentic AI frameworks and orchestration tools.

Monitoring, Observability & Operations

Implement logging, metrics, tracing, and alerting for AI services.
Monitor model performance, drift, latency, and availability.
Provide on-call production support and incident resolution.

Security, Governance & Compliance

Implement IAM, secrets management, encryption, and network security.
Ensure compliance with enterprise governance and audit requirements.

Qualifications & Experience

5+ years experience in MLOps, AI Engineering, or Platform Engineering.

Strong Python and Linux experience.

Experience deploying AI systems in production environments.

Preferred Skills

Experience with ML platforms such as MLflow, Kubeflow, SageMaker, or Azure ML.(These are MLOps Frameworks)

Experience with high-availability AI platforms.

Familiarity with ITIL or enterprise service management processes.

Location

Sydney

Job Function

TECHNOLOGY

Role

Engineer

Job Id

420572

Desired Skills

Artificial Intelligence | Machine Learning

Apply Now

Refine Your Search

security platform engineer secrets jobs

MLOps / AI Engineer

Senior Platform Engineer

Staff Engineer (React)

Senior Aerodynamics Engineer, Omen

Vulnerability Operations Engineer

Senior DevSecOps Engineer

Engineering Lead, AWS Kubernetes Platform

AI DevOps Engineer

GitHub Architect – DevOps

Senior DevOps Engineer

Senior Systems Administrator (Infrastructure Engineer)

DevOps Lead

Senior DevSecOps Engineer

Vulnerability Management Specialist

Senior DevSecOps Engineer

Cyber Security Manager

Aircraft Maintenance Engineer (Avionics) - P-8A Poseidon or MC-55A Peregrine

Identity & PAM Technical Lead (IIQ + Delinea)

Senior DevOps Engineer

Regional Deployment Engineer

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