Engineer (50510)

Company Overview

Incedo is a US-based consulting, data science and technology services firm with over 3000 people helping clients

from our six offices across US, Mexico and India. We help our clients achieve competitive advantage through

end-to-end digital transformation. Our uniqueness lies in bringing together strong engineering, data science, and

design capabilities coupled with deep domain understanding. We combine services and products to maximize

business impact for our clients in telecom, Banking, Wealth Management, product engineering and life science

& healthcare industries.

Working at Incedo will provide you an opportunity to work with industry leading client organizations, deep

technology and domain experts, and global teams. Incedo University, our learning platform, provides ample

learning opportunities starting with a structured onboarding program and carrying throughout various stages of

your career. A variety of fun activities is also an integral part of our friendly work environment. Our flexible

career paths allow you to grow into a program manager, a technical architect or a domain expert based on your

skills and interests.

Our Mission is to enable our clients to maximize business impact from technology by

• Harnessing the transformational impact of emerging technologies
• Bridging the gap between business and technology

Role Description

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.

Technical Skills

Nice-to-have skills

Qualifications

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.

Company Value

We value diversity at Incedo. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.