MLOps Engineer

Insight Global; Chicago (IL); On-site; USD 110,000 - 170,000; Full time

Job summary

Insight Global is seeking an MLOps Engineer to support Data Science and Software Engineering teams. You will deploy, maintain, and automate machine learning workflows and pipelines in the cloud, applying software engineering best practices to productionize models and keep them updated via CI/CD.

You will build automation with GitHub Actions, containerize with Docker, and orchestrate via Kubernetes. Expect collaboration across teams and ongoing monitoring of model performance in production

Qualifications

• 2–4 years of professional software development with focus on solid design, clean code, and automated tests.
• Proficiency in Python for APIs, data processing, and tooling.
• Experience deploying and maintaining ML workflows in the cloud and in production.
• Understanding of ML lifecycle, training-to-serving, and ML frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch).
• Experience with CI/CD, promotion gates, and release management for ML systems.

Responsibilities

• Deploy, maintain, and automate ML workflows and pipelines.
• Apply software engineering best practices to productionize models in cloud environments.
• Build and improve CI/CD pipelines for ML workflows and model updates.
• Collaborate with Data Science and Software Engineering teams to ensure reliable deployments.
• Utilize Docker and Kubernetes to containerize workloads and orchestrate services.
• Monitor performance and reliability of ML systems in production.

Skills

Python

CI/CD

Docker/Kubernetes

ML Frameworks

GitHub Actions

Azure Cloud

Spark/Databricks

IaC

GenAI

Agentic AI

LLM Workflows

Tools

Docker

Kubernetes

Azure

MLflow

AzureML

Grafana

Pinecone

Milvus

Chroma

Terraform

CloudFormation

Job description

Job Description

We are seeking an MLOps Engineer to support our Data Science and SoftwareEngineering teams. In this role, you will be responsible for deploying, maintaining, andautomating machine learning workflows and pipelines. You will apply softwareengineering best practices to ensure our machine learning models are smoothlyintegrated into production, regularly updated via CI/CD, and monitored for performancein our cloud environment

Skills and Requirements

• Software Engineering: 2–4 years of experience in professional softwaredevelopment with a focus on demonstrating strong system design capabilities,clean code practices (SOLID principles), and robust automated testingparadigms.
• Python Development: Strong proficiency in Python, including experiencebuilding APIs, libraries, and processing data.
• Cloud Applications: Practical experience in developing and deployingapplications in cloud (specifically Azure, etc.) and utilizing their native managedML and infrastructure services.
• ML Concepts & Ecosystems: Solid understanding of the machine learninglifecycle, training-to-serving workflows, and familiarity with frameworks likeScikit-Learn, TensorFlow, or PyTorch.
• CI/CD & DevOps: Proven background establishing automation pipelines,promotion gates, and release mechanics geared towards machine learningsystems.
• Containers & Orchestration: Hands on experience with Docker forcontainerising workloads and Kubernetes for orchestrating microservices anddistributed deployments.
• Production grade GenAI: Experience in building production grade LargeLanguage Model (LLM) workflows, Retrieval-Augmented Generation (RAG)pipelines, and integrating vector databases (e.g., Pinecone, Milvus, Chroma)Agentic AI & Orchestration: Exposure to or hands-on experience building anddeploying multi-agent AI systems, autonomous workflows, and agenticarchitectures using frameworks like Microsoft Agentic Framework, LangGraph,CrewAI, AutoGen, or LlamaIndex.
• Experience configuring and managing automated workflows within GithubActions
• Hands-on experience processing distributed datasets and building pipelines viaApache Spark and Databricks environments.
• Familiarity with o SRE/MLOps tools such as MLflow ,AzureML, Grafana
• Infrastructure as Code (IaC): Practical knowledge utilizing automation toolssuch as Terraform or CloudFormation to provision predictable environments.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [e-mail].