Job Description
Design, develop, and deploy scalable ML solutions in production environments
Collaborate with cross-functional teams to integrate ML models into business applications
Build and maintain data pipelines and orchestration workflows
Monitor and optimize ML systems for performance, reliability, and cost-efficiency
Develop APIs and services to support ML applications
Contribute to CI/CD processes and infrastructure for ML deployment
Provide technical leadership and mentorship to junior engineers
Stay current with emerging technologies and best practices in AI/ML engineering
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 opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their 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 recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
Bachelor’s degree or equivalent and 4+ years of experience in machine learning, software engineering, or data engineering
Experience building CI/CD with automation components
Hands-on experience with Databricks (This will serve as ML Platform)
Hands-on experience with Terraform
Hands-on experience with Kubernetes in multi-tenant environments
Understanding of operational aspects of DevOps (Licenses, Authorizations, etc)
Strong Cloud knowledge and experience (Azure preferred)
Need to have knowledge of how to set up a platform in a Centralized capacity
3+ years of experience with SQL
Monitoring of systems such as Dynatrace
3+ years of programming experience in Python, C, C++, Spark, Scala, and/or Java
Experience working within a matrix organization and managing internal/external relationships
Strong problem-solving skills with the ability to diagnose and resolve complex issues
2+ years of experience contributing to financial decisions
2+ years of leadership experience (direct, indirect, or cross-functional)
Willingness to travel up to 10% for business purposes
Nice to Have Skills & Experience
Graduate degree in a technical discipline
Experience deploying ML models at scale using open-source tools (e.g., Kubeflow, Seldon)
Experience with DAG-based orchestration systems (Airflow, Prefect)
Experience with data pipelines using Apache Spark or Databricks
Familiarity with ML registries (MLFlow)
Experience with CI/CD pipelines (Tekton, Azure DevOps, GitHub Actions)
Strong troubleshooting skills for distributed systems and performance optimization
Experience writing and deploying production-grade Python applications and libraries
Experience deploying and maintaining event-driven and reactive ML applications
Experience with batch and streaming ML deployment systems
Experience with REST API development
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.