Senior DevOps Engineer – Azure & Databricks (AI/ML Focus) at Acuity Analytics

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Full Time

Start Date

Immediate

Expiry Date

11 Apr, 26

Salary

0.0

Posted On

11 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Databricks, MLFlow, Unity Catalog, DevOps, CI/CD, Pipeline Automation, Data Architecture, Schema Evolution, Governance, Infrastructure as Code, Terraform, Machine Learning, Generative AI, Containerization, Docker, Kubernetes

Industry

IT Services and IT Consulting

Description

The creative mind behind every project. Put your skills to the test to build solutions that continue to shape the world we live in. About Us Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We delivers deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency. Please note that this role is currently available for European residents. About the role We are seeking a Senior DevOps Engineer with expertise in Azure Databricks and cloud-native AI/ML operations. You will be a key contributor to a next-generation AI platform built on Azure Databricks, enabling data scientists and engineers to train, deploy, monitor, and govern ML and GenAI models efficiently. This role blends MLOps best practices, cloud-native architecture, and Databricks expertise to ensure AI models are production-ready, scalable, and compliant with enterprise standards. Key Responsibilities Design, implement, and optimize ML/AI pipelines for training, deployment, monitoring, and governance. Leverage Azure Databricks capabilities including MLFlow for experiment tracking and Unity Catalog for data governance. Build and maintain CI/CD pipelines as well as automated ModelOps workflows for AI/ML applications. Ensure data architecture supports schema evolution, governance, and compliance requirements. Operate in a cloud-native Azure environment to deliver robust and scalable ML solutions. Required Skills & Experience Proven experience with Azure Databricks, including MLFlow and Unity Catalog. Strong background in DevOps for ML/AI, including CI/CD and pipeline automation. Solid understanding of data architecture, schema evolution, and governance principles. Experience working in Microsoft Azure or similar cloud environments. Hands-on experience with Infrastructure as Code (IaC) using Terraform. Nice to Have High-level understanding of machine learning and generative AI concepts and workflows. Solid knowledge of containerization (Docker) and orchestration (Kubernetes). Experience in Python software development and scripting. Hands-on experience with TensorFlow, PyTorch, and Scikit-learn in a Databricks environment. Why join us? People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Check out this page for more details. If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics. For more details about life at Ascent, check out our Life Page here. Ascent is now an Acuity Analytics. Read here.

Responsibilities

Design, implement, and optimize ML/AI pipelines for training, deployment, monitoring, and governance. Operate in a cloud-native Azure environment to deliver robust and scalable ML solutions.