Senior Machine Learning Engineer

Job Description

Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We

are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business

and technology across Banking & Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences.

We are building Incedo 4.0 - an AI-native, execution-focused, founder-led organization designed for scale, speed,

and long-term impact.

Incedo delivers ROI from AI @ Scale through the “Power of 3”:

• Deep domain expertise

• AI & Data capabilities

• Engineering & Operations excellence.

Role : Senior Machine Learning Engineer

Location: Cincinnati OH (3days onsite)

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.

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.
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• Champion an automation-first approach to software and AI engineering, identifying opportunities to improve operational efficiency and reduce manual processes.
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• Build and operationalize machine learning models and AI-enabled applications throughout the entire model lifecycle, from experimentation to production deployment and monitoring.
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• Develop and deploy Generative AI applications in production environments, preferably within financial services or other highly regulated industries.
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• Apply and advocate Responsible AI principles , ensuring solutions meet requirements for fairness, explainability, transparency, privacy, security, and compliance.
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• Perform model risk evaluations , complete required governance documentation and questionnaires, and partner with stakeholders to address and remediate identified risks.
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• Establish and maintain frameworks for MLOps, model lifecycle management, monitoring, validation, version control, auditability, and AI governance .
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• Collaborate with Risk, Compliance, Information Security, and business partners to ensure machine learning solutions meet enterprise and regulatory standards.
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• Implement CI/CD pipelines, automated testing, model monitoring, observability, and production support processes for machine learning applications.
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• Evaluate emerging machine learning and AI technologies and recommend appropriate adoption strategies.
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• 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
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• Extensive experience designing, developing, and deploying machine learning solutions in production environments.
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• Hands-on experience developing and deploying Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI development frameworks.
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• Strong understanding of machine learning model development, feature engineering, model evaluation, performance optimization, and model monitoring.
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• Experience conducting model risk assessments and supporting governance, compliance, and validation requirements within regulated environments.
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• Practical experience implementing MLOps practices including model deployment, versioning, monitoring, automated retraining, and CI/CD pipelines.
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• Strong understanding of Responsible AI, model explainability, governance, and risk management concepts.
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• Proficiency in Python and modern machine learning ecosystems, including frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or equivalent technologies.
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• Strong communication, problem-solving, and stakeholder management skills.
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