1 day ago
Washington, DC, USAStaff+
Base Salary
$90k - $150k/yr
Responsibilities
- Design, develop, validate, deploy, and optimize predictive, classification, clustering, anomaly detection, forecasting, risk, and other machine learning models using Python and PySpark.
- Build Generative AI, RAG, NLP, LLM, conversational AI, and agent-based solutions using Azure OpenAI Service, LangChain, LangGraph, and agentic AI frameworks.
- Develop scalable FastAPI backend services, APIs, microservices, authentication integrations, monitoring, logging, and reusable AI application components.
- Create Azure-based data pipelines, feature engineering workflows, model monitoring, retraining, experiment tracking, governance, and lifecycle management processes.
- Collaborate with product owners, business analysts, operations teams, and technology stakeholders to translate financial business challenges into analytical solutions.
- Promote responsible AI practices covering fairness, explainability, bias, security, data quality, model risk, documentation, and regulatory requirements.
- Mentor junior data scientists, machine learning engineers, and developers while promoting software engineering, experimentation, MLOps, and AI governance best practices.
Requirements
- 8+ years of experience in data science, machine learning, AI engineering, or related fields.
- Expert proficiency in Python and PySpark for large-scale data processing and model development.
- Strong experience with FastAPI, REST APIs, microservices architecture, object-oriented programming, and software engineering best practices.
- Hands-on experience with LangChain, LangGraph, RAG architectures, agentic AI frameworks, and LLM application development.
- Strong expertise in Azure Machine Learning, Azure OpenAI Service, Azure Databricks, Azure Data Lake, MLOps, and CI/CD practices.
- Deep understanding of supervised and unsupervised learning, deep learning, ensemble methods, NLP, time-series forecasting, anomaly detection, risk modeling, model evaluation, feature engineering, experimentation, validation, and explainability.
- Experience developing and deploying enterprise AI/ML solutions in cloud environments.
- Experience supporting investment banking, capital markets, brokerage operations, trade surveillance, risk management, or front-office and middle-office functions.
- Strong communication, stakeholder management, analytical, problem-solving, and technical explanation skills.
- Preferred experience with Pinecone, Azure AI Search, Weaviate, ChromaDB, Docker, Kubernetes, CI/CD pipelines, DevOps, responsible AI, model risk management, AI governance frameworks, or Azure AI, Data Science, or Machine Learning certifications.
Benefits
- Remote position.
- Medical, dental, vision, and life insurance.
- Paid holidays and paid time off.
- 401(k) plan and contributions.
- Long-term and short-term disability coverage.
- Paid parental leave.
- Employee Stock Purchase Plan.
- Eligible for a discretionary annual incentive program based on performance and applicable plan terms.
Tech Stack
Categories
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.