Senior Machine Learning Engineer

Incedo Inc.; Cincinnati (OH); Hybrid; USD 120,000 - 165,000; Full time

Job summary

Incedo Inc. is seeking a Senior Machine Learning Engineer in Cincinnati, OH, with a strong bias for action and an ownership mindset. The role focuses on delivering enterprise-grade ML and Generative AI solutions, including production-grade models, MLOps practice, and governance in regulated environments.

You will drive automation, implement CI/CD pipelines, and collaborate with Risk, Compliance, and Security teams to ensure regulatory alignment and business value.

Qualifications

• Extensive experience designing, developing, and deploying ML solutions in production.
• Hands-on experience with Generative AI using LLMs, RAG, vector databases, and modern frameworks.
• Strong understanding of ML model development, feature engineering, evaluation, and monitoring.
• Experience conducting model risk assessments in regulated environments.
• Practical MLOps implementation including deployment, versioning, monitoring, retraining, and CI/CD.
• Strong understanding of Responsible AI, explainability, governance and risk concepts.
• Proficiency in Python and ML ecosystems (TF, PyTorch, Scikit-learn, LangChain, Semantic Kernel).
• Excellent communication, problem-solving, and stakeholder skills.

Responsibilities

• Design, develop, deploy, and maintain scalable ML and Generative AI solutions.
• Champion an automation-first approach to software and AI engineering.
• Build and operationalize ML models and AI-enabled apps end-to-end.
• Develop and deploy Generative AI apps in production, esp. in regulated sectors.
• Apply Responsible AI principles, ensuring fairness, explainability, privacy and security.
• Perform model risk evaluations and coordinate governance documentation.
• Establish and maintain ML lifecycle, monitoring, audits, and AI governance frameworks.
• Collaborate with Risk, Compliance, and Information Security teams.
• Implement CI/CD, automated testing, monitoring, observability, and production support.
• Evaluate emerging ML/AI technologies and adoption strategies.
• Mentor team members on ML engineering, MLOps, and production AI systems.

Skills

Python

MLOps

Generative AI

LLMs

RAG

CI/CD

Explainability

Regulated environments

Tools

TensorFlow

PyTorch

Scikit-learn

LangChain

Semantic Kernel

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":

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

• 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.

Required Qualifications

• Extensive experience designing, developing, and deploying machine learning solutions in production environments.
• 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.
• 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.