AI/ML Engineer

Job Description

Insight Global is hiring an experienced Machine Learning Engineer to support one of its largest financial services clients. In this role, you will help architect, deploy, and scale Generative AI solutions in production environments. Working alongside data scientists and engineering teams, you will be responsible for operationalizing AI models, supporting cloud-based AI infrastructure, and ensuring solutions are reliable, scalable, secure, and cost-effective. The ideal candidate combines a strong machine learning foundation with experience building and supporting modern GenAI applications and platforms.

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 View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

- 5+ years of experience as a Machine Learning Engineer deploying and supporting models in production environments.

- Strong understanding of Generative AI technologies and architectures, including LLMs, RAG, vector databases, prompt engineering, and agent/multi-agent systems.

- Experience deploying, monitoring, and scaling AI/ML or GenAI solutions in cloud environments, preferably AWS.

- Hands-on experience with data pipelines, MLOps, CI/CD automation, Infrastructure as Code (Terraform/CloudFormation), and containerization technologies such as Docker and Kubernetes.

- Experience developing AI solutions that integrate with APIs, enterprise systems, and external data sources.

- Strong understanding of AI security, monitoring, performance optimization, and cost management best practices.

- Proficiency in Python and modern AI frameworks such as Hugging Face and LangChain.

Ability to learn quickly and adapt to emerging AI technologies. - Master's degree in Computer Science, Engineering, Data Science, or a related field.

- Experience with semantic layers, ontologies, or knowledge graphs.

Experience with AI testing, evaluation frameworks, or harness engineering.