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Job Description
Job Description Insight Global is hiring a highly skilled and experienced senior machine learning engineer for one of their largest clients in the financial industry. The ideal candidate will have extensive, hands‑on experience developing and deploying production‑scale GenAI systems. They must have owned a GenAI project end‑to‑end, from initial development through production deployment, and bring a strong engineering background with the ability to scale, optimize, and deploy AI models in real‑world environments. The candidate should have strong AWS experience as well as advanced Python skills. 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.
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At least a bachelor's degree in Computer Science/Engineering, Data Science, or a related field.
5+ years of experience as a machine learning engineer deploying models in production and managing the model lifecycle.
Must have experience working end‑to‑end putting an agentic solution into production.
Strong proficiency in Python.
Experience with cloud platforms — specifically AWS.
Must be able to deploy, monitor, and maintain GenAI models in production, ensuring they function reliably in real‑world settings.
Expertise in GenAI frameworks, prompt engineering, and model serving. Deep understanding of LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized infrastructure for GenAI workloads.
Master's degree in Computer Science/Engineering, Data Science, or a related field.
Experience with Azure and GCP, containerization (Docker), and infrastructure management (Terraform).