ML Ops and DevOps Engineer

Job Overview

DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.

The ML Ops and DevOps Engineer is a specialised technical role focused on bridging the gap between AI development and production-grade operations. You will design, deploy, and manage scalable AI solutions primarily across AWS and Azure environments, integrating Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps).

Key Responsibilities

• Design and deploy scalable AI infrastructure using GitHub Actions, EKS, ECS, and AWS Lambda; automate all resource provisioning via Terraform.


• Create and manage end-to-end CI/CD pipelines for model deployment, versioning, and lifecycle management using Azure DevOps and GitHub Actions.


• Deploy machine learning and large language models via Amazon SageMaker, EKS, and Azure ML Endpoints.


• Implement comprehensive monitoring for model performance and drift using Amazon CloudWatch, SageMaker Model Monitor, and OpenSearch.


• Integrate advanced services including Azure OpenAI, Azure Cognitive Services, and AWS Rekognition into enterprise workflows.


• Design robust data pipelines and real-time ingestion streams using AWS Glue, Amazon Redshift, Athena, and Apache Spark.


• Enforce cloud security through AWS WAF, Azure Key Vault, and RBAC, ensuring all deployments meet GDPR and ISO compliance standards.


• Supervise team activities and contribute to change initiatives in line with the Bank’s continuous improvement standards.

Required Qualifications

What we need from you:

• A Bachelor’s degree in Computer Science, AI, Software Engineering, Statistics, Mathematics, or a related quantitative field.


• A minimum of 5 years in designing and deploying AI solutions in cloud environments, specifically within MLOps/LLMOps frameworks.


• Proficiency with GitHub Actions, Spark, Redshift, MongoDB, and Azure Purview.


• Deep hands-on expertise in AWS (SageMaker, EKS, S3) and Azure (OpenAI, Cognitive Services) ecosystems.


• Mastery of Terraform for multi-cloud resource automation.


• Proven experience in both MLOps (standard ML) and LLMOps (Large Language Models), focusing on fine-tuning, orchestration, and monitoring.


• Expertise in managing container images via ECR/ACR and deploying via Kubernetes (EKS/AKS).


• Strong understanding of secure networking (WAF, NSGs) and secret management.

Benefits & Growth Opportunities

Competitive salary.
Visa Sponsorship for the successful individual.
Comprehensive health insurance for the successful individual.
Professional development and certification support.
Opportunity to work on cutting-edge AI projects.
Career advancement opportunities in a rapidly growing AI company.

About DeepLight AI

At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.

Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.