Senior Machine Learning Engineer

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.

Pay: $120,000.00 - $130,000.00 per year

Work Location: In person