OneMain Financial Jobs

We are seeking a skilled machine learning platform engineer (MLOps) to join our agile platform team. In this role, you’ll contribute across the entire lifecycle - from concept to deployment and collaborate closely with cross-functional teams to deliver high-quality digital solutions. Further, you will drive the orchestration of advanced agentic workflows to enable autonomous, AI-driven systems. You will be responsible for engineering robust data pipelines, establishing comprehensive model management lifecycles, overseeing all foundational platform-level AI integrations.

Job Responsibilities

• Design, develop and deploy machine learning solutions and services

• Implement end-to-end machine learning pipelines from data ingestion to training and model serving

• Operationalize LLMs, embeddings, and multi-agent systems in real-world applications

• Manage the machine learning and model lifecycle (experimentation, registry, deployment)

• Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production

• Containerize applications using Docker and orchestrate them via Kubernetes

• Build and maintain CI/CD pipelines for ML models and LLM applications

• Collaborate with data scientists to refactor research code into production-ready Python code

• Monitor model performance, data drift, and performance in production

• Assess and integrate AI solutions ensuring optimal performance and reliability

• Design and implement production grade RAG systems

• Collaborate with infrastructure teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes

• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions

Job Requirements

Competencies

• Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization

• Ability to manage personal workloads effectively, to prioritize tasks, manage timelines, and deliver high-quality results on schedule

• Continuous learning mindset, with a passion for staying up to date with the latest advancements in machine learning and artificial intelligence

• Attention to detail and commitment to producing high-quality, reliable, and maintainable code

Skills requirements

• Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code

• DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration

• Practical understanding of GPU architecture and cloud compute instances to optimize resource allocation for training and inference workloads

• MLOPS tools: hands on experience with MLflow (or similar tools like weights & biases) for experiment tracking and model registry

• Proven experience working with Large Language Models (LLMs)

• Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns

• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques

• Hands-on experience with CI/CD pipelines (GitLab, Jenkins)

• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization

• Excellent problem-solving and debugging skills, with the ability to identify and resolve issues quickly and effectively

• Relevant work experience in machine learning, data science or a related field

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Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.