Senior Machine Learning Engineer in Cincinnati
Job Description
Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We
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are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business
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and technology across Banking & Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences.
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We are building Incedo 4.0 - an AI-, execution-focused, founder-led organization designed for scale, speed,
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and long-term impact.
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Incedo delivers ROI from AI @ Scale through the “Power of 3”:
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• Deep domain expertise
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• AI & Data capabilities
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• Engineering & Operations excellence.
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Role : Senior Machine Learning Engineer
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Location: Cincinnati OH (3days onsite)
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We are seeking an experienced Machine Learning Engineer with a strong bias for action, an ownership mindset, and a passion for solving complex business problems through automation and AI. The ideal candidate demonstrates technical excellence, leads by example, and has proven experience delivering enterprise-grade machine learning and Generative AI solutions in regulated environments.
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Key Responsibilities
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- Design, develop, deploy, and maintain scalable machine learning and Generative AI solutions with a focus on reliability, performance, security, and business value.
- Champion an automation-first approach to software and AI engineering, identifying opportunities to improve operational efficiency and reduce manual processes.
- Build and operationalize machine learning models and AI-enabled applications throughout the entire model lifecycle, from experimentation to production deployment and monitoring.
- Develop and deploy Generative AI applications in production environments, preferably within financial services or other highly regulated industries.
- Apply and advocate Responsible AI principles, ensuring solutions meet requirements for fairness, explainability, transparency, privacy, security, and compliance.
- Perform model risk evaluations, complete required governance documentation and questionnaires, and partner with stakeholders to address and remediate identified risks.
- Establish and maintain frameworks for MLOps, model lifecycle management, monitoring, validation, version control, auditability, and AI governance.
- Collaborate with Risk, Compliance, Information Security, and business partners to ensure machine learning solutions meet enterprise and regulatory standards.
- Implement CI/CD pipelines, automated testing, model monitoring, observability, and production support processes for machine learning applications.
- Evaluate emerging machine learning and AI technologies and recommend appropriate adoption strategies.
- Mentor team members on best practices in machine learning engineering, MLOps, Responsible AI, and production AI systems.
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Required Qualifications
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- Experience level will be 8-12 years
- Extensive experience designing, developing, and deploying machine learning solutions in production environments.
- Hands-on experience developing and deploying Generative AI applications using Large Models (LLMs), Retrieval-Augmented (RAG), vector databases, and modern AI development frameworks.
- Strong understanding of machine learning model development, feature engineering, model evaluation, performance optimization, and model monitoring.
- Experience conducting model risk assessments and supporting governance, compliance, and validation requirements within regulated environments.
- Practical experience implementing MLOps practices including model deployment, versioning, monitoring, automated retraining, and CI/CD pipelines.
- Strong understanding of Responsible AI, model explainability, governance, and risk management concepts.
- Proficiency in Python and modern machine learning ecosystems, including frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or equivalent technologies.
- Strong communication, problem-solving, and stakeholder management skills.
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