Job Description
We are looking for a hands-on AI/ML Engineer to design, build, and scale intelligent applications that drive real business impact. This role will focus on developing and deploying machine learning models and LLM-powered solutions within a modern, cloud-native environment.
You’ll work across the full lifecycle—from model development to production deployment—ensuring solutions are scalable, observable, and aligned with enterprise needs.
PR: $70-$85hr
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
Strong experience in software engineering, with proficiency in:
Python (required)
JavaScript (preferred)
Experience working in Kubernetes/containerized environments
Hands-on experience with machine learning model development, deployment, and lifecycle management
Experience building or integrating LLM-based applications (chatbots, copilots, or similar AI tools)
Familiarity with CI/CD pipelines, including tools such as GitHub Actions
Experience operating within an Agile development environment
Knowledge of production observability, including monitoring, logging, and performance tuning for ML systems and applications
Nice to Have Skills & Experience
Experience with MLOps frameworks and tools
Familiarity with cloud platforms (AWS, Azure, or GCP)
Experience with data engineering workflows and pipelines
Exposure to RAG (retrieval-augmented generation) or agent-based AI systems
Understanding of model governance, versioning, and compliance
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.