Manager - ML Engineer - IN

The role leverage big data tools and programming frameworks to ensure that the raw data gathered from data pipelines are redefined as data science models that are ready to scale as needed.

Key Responsibilities And Duties

• Machine learning engineers feed data into models defined by data scientists.
• They’re also responsible for taking theoretical data science models and helping scale them out to production-level models that can handle terabytes of real-time data.
  
  

Educational Requirements

• University (Degree) Preferred
  
  

Work Experience

• 5+ Years Required; 7+ Years Preferred
  
  

Physical Requirements

• Physical Requirements: Sedentary Work
  
  

Career Level

9PL

Role Overview

Lead a high-performing engineering team responsible for building distributed, scalable, and low-latency applications on AWS using Python. The role involves hands-on development, architecture design, and AI/ML integration—spanning the full SDLC, data management, and emerging Generative AI technologies.

Key Responsibilities

Application & Cloud Development

• Architect and build large-scale Python applications using frameworks such as containers, FastAPI, optimized for low latency and scalability.
• Design and manage cloud-native solutions leveraging AWS services (Lambda, Glue jobs, S3, SQS, SNS, DynamoDB, EKS, CloudFront, IAM etc.).
  
  

Data Engineering & Management

• Design and maintain data ingestion and processing pipelines for structured and unstructured data.
• Work with relational (PostgreSQL, SQL Server) and non-relational (DynamoDB, MongoDB) databases, and data lakes.
• Collaborate with data and analytics teams to ensure data integrity, lineage, and availability.
  
  

DevOps & SDLC

• Drive the full software development lifecycle including CI/CD automation, testing, container orchestration, and monitoring.
• Implement DevOps practices using Docker, Kubernetes, Terraform, GitHub Actions, or Jenkins.
• Ensure efficient, secure, and reproducible deployments across environments.
  
  

AI, ML & GenAI Development

• Develop and deploy machine learning and deep learning models for business and analytical use cases.
• Build Generative AI solutions, including:
• RAG (Retrieval-Augmented Generation) pipelines
• Prompt engineering and LangGraph/agentic AI frameworks
• LLM fine-tuning, reinforcement training, and performance benchmarking
• Observability frameworks for model monitoring and traceability
• Collaborate with data scientists to move models from experimentation to production at scale.
  

Governance, Security & Compliance

• Implement and enforce best practices for data governance, cybersecurity, and compliance.
• Apply IAM, encryption, and network security principles to protect sensitive data.
• Align all development and data processes with enterprise risk and regulatory standards.
  
  

Related Skills

Collaboration, Continuous Improvement Mindset, Data-Driven Business Intelligence, Data Engineering/Analytics, Data Visualization, Predictive Modeling, Problem Solving, Programming, Resourcefulness, Statistics, Story Telling

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Company Overview

TIAA Global Capabilities was established in 2016 with a mission to tap into a vast pool of talent, reduce risk by insourcing key platforms and processes, as well as contribute to innovation with a focus on enhancing our technology stack. TIAA Global Capabilities is focused on building a scalable and sustainable organization , with a focus on technology , operations and expanding into the shared services business space.

Working closely with our U.S. colleagues and other partners, our goal is to reduce risk, improve the efficiency of our technology and processes and develop innovative ideas to increase throughput and productivity.

We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other legally protected status.

Our Culture of Impact

At TIAA, we're on a mission to build on our 100+ year legacy of delivering for our clients while evolving to meet tomorrow's challenges. We equip our associates with future-focused skills and AI tools that enable us to advance our mission. Together, we are fighting to ensure a more secure financial future for all and for generations to come. We are guided by our values: Champion Our People, Be Client Obsessed, Lead with Integrity, Own It, and Win As One. They influence every decision we make and how we work together to serve our clients every day. We thrive in a collaborative in-office environment where teams work across organizational boundaries with shared purpose, accelerating innovation and delivering meaningful results. Our workplace brings together TIAA and Nuveen's entrepreneurial spirit, where we work hard and work together to create lasting impact. Here, every associate can grow through meaningful learning experiences and development pathways—because when our people succeed, our impact on clients' lives grows stronger.

Accessibility Support

TIAA offers support for those who need assistance with our online application process to provide an equal employment opportunity to all job seekers, including individuals with disabilities.

If You Are a U.S. Applicant And Desire a Reasonable Accommodation To Complete a Job Application Please Use One Of The Below Options To Contact Our Accessibility Support Team

Phone: (800) 842-2755

Email: accessibility.support@tiaa.org

Privacy Notices

For Applicants of TIAA, Nuveen and Affiliates residing in US (other than California), click here.

For Applicants of TIAA, Nuveen and Affiliates residing in California, please click here.

For Applicants of TIAA Global Capabilities, click here.

For Applicants of Nuveen residing in Europe and APAC, please click here.

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Role Overview

Lead a high-performing engineering team responsible for building distributed, scalable, and low-latency applications on AWS using Python. The role involves hands-on development, architecture design, and AI/ML integration—spanning the full SDLC, data management, and emerging Generative AI technologies.

Key Responsibilities

Application & Cloud Development

• Architect and build large-scale Python applications using frameworks such as containers, FastAPI, optimized for low latency and scalability.
• Design and manage cloud-native solutions leveraging AWS services (Lambda, Glue jobs, S3, SQS, SNS, DynamoDB, EKS, CloudFront, IAM etc.).
  
  

Data Engineering & Management

• Design and maintain data ingestion and processing pipelines for structured and unstructured data.
• Work with relational (PostgreSQL, SQL Server) and non-relational (DynamoDB, MongoDB) databases, and data lakes.
• Collaborate with data and analytics teams to ensure data integrity, lineage, and availability.
  
  

DevOps & SDLC

• Drive the full software development lifecycle including CI/CD automation, testing, container orchestration, and monitoring.
• Implement DevOps practices using Docker, Kubernetes, Terraform, GitHub Actions, or Jenkins.
• Ensure efficient, secure, and reproducible deployments across environments.
  
  

AI, ML & GenAI Development

• Develop and deploy machine learning and deep learning models for business and analytical use cases.
• Build Generative AI solutions, including:
• RAG (Retrieval-Augmented Generation) pipelines
• Prompt engineering and LangGraph/agentic AI frameworks
• LLM fine-tuning, reinforcement training, and performance benchmarking
• Observability frameworks for model monitoring and traceability
• Collaborate with data scientists to move models from experimentation to production at scale.
  

Governance, Security & Compliance

• Implement and enforce best practices for data governance, cybersecurity, and compliance.
• Apply IAM, encryption, and network security principles to protect sensitive data.
• Align all development and data processes with enterprise risk and regulatory standards.