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Senior ML Engineer

Job

Insight Global

Cleveland, OH (In Person)

$161,200 Salary, Full-Time

Posted 2 days ago (Updated 11 hours ago) • Actively hiring

Expires 7/6/2026

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Job Description

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.

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Insight Global's Workforce Privacy Policy:
https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 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 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