AI/ML Engineer

Vanguard; Malvern (Chester County); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Vanguard's Corporate Services division is seeking a Machine Learning/AI Engineer to design, build, and scale enterprise AI/ML solutions across the company. You will partner with business stakeholders and engineers to translate challenges into data-driven solutions.

The role emphasizes production-grade deployments on AWS, MLOps, knowledge graphs, Generative AI, and governance. You will mentor teammates and stay current with emerging AI technologies, delivering reliable, scalable AI applications.

Qualifications

• Bachelor's degree in a technical field.
• 6+ years of experience in ML/DS/engineering.
• 3+ years building scalable data pipelines and ETL using AWS.
• Strong Python and software engineering practices.
• Production-grade AI solution delivery in cloud environments (AWS preferred).

Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions.
• Build scalable, cloud-native AI apps using AWS tech (SageMaker, ECS, Lambda, S3).
• Develop ML pipelines for batch and real-time workloads.
• Design and implement Generative AI using LLMs, vector databases, and knowledge retrieval systems.
• Partner with stakeholders to translate business problems into AI solutions.
• Establish data lineage, data quality, and monitoring for models.
• Ensure governance, security, and Responsible AI compliance.

Skills

Python

Machine Learning

Data Engineering

Software Engineering

AWS

SageMaker

MLOps

Docker

Kubernetes

Generative AI

LLMs

Data pipelines

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related field

Master's degree preferred

Tools

Docker

Kubernetes

SageMaker

EventBridge

Lambda

S3

EC2

CI/CD pipelines

Job description

At Vanguard's Corporate Services division, we are seeking a Machine Learning/ AI Engineer to design, build, and scale enterprise AI/ML solutions that drive business innovation and support the development, deployment, and operationalization of intelligent applications. The ideal candidate combines strong software engineering, machine learning, and cloud expertise with hands-on experience delivering production-grade AI solutions. This role will partner closely with business stakeholders, product teams, and engineers to solve complex business problems using machine learning, Generative AI, and advanced analytics.

Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions, including data ingestion, feature engineering, model training, deployment, monitoring, and lifecycle management.
• Build scalable, cloud-native AI/ML applications and services using AWS technologies such as SageMaker, ECS, Lambda, S3, EventBridge, and Step Functions.
• Develop and maintain machine learning, data engineering, and MLOps pipelines supporting batch and real-time workloads.
• Design and implement Generative AI solutions leveraging Large Language Models (LLMs), Advanced RAG, vector databases, knowledge retrieval systems, agentic AI frameworks, and fine-tuning techniques.
• Design and utilize knowledge graphs, graph databases, and relationship-based analytics to enhance enterprise intelligence and decision-making.
• Partner with business stakeholders to translate business challenges into scalable analytical and AI-driven solutions.
• Conduct data discovery and exploratory analysis, establish data lineage, and perform root cause analysis to ensure data quality and reliability.
• Implement model monitoring, observability, alerting, and operational support processes for production AI/ML solutions.
• Ensure adherence to enterprise AI governance, security, Responsible AI, privacy, and model risk management standards.
• Serve as a machine learning engineering subject matter expert, lead technical design discussions, and mentor team members on AI/ML best practices.
• Stay current on emerging AI technologies and evaluate their application to business opportunities.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field; Master's degree preferred.
• 6+ years of experience in Machine Learning Engineering, Data Engineering, Software Engineering, or a related discipline.
• 3+ years of hands-on experience building scalable data pipelines and ETL solutions using AWS services.
• Strong proficiency in Python and modern software engineering practices.
• Experience deploying and supporting production-grade AI/ML applications in cloud environments, preferably AWS.
• Strong experience with SageMaker, MLOps, CI/CD pipelines, model deployment, monitoring, and Machine Learning Development Lifecycle (MDLC) practices.
• Experience with containerization and orchestration technologies such as Docker, ECS, and Kubernetes.
• Experience with Generative AI technologies, including LLMs, Advanced RAG, vector databases, semantic search, agentic AI frameworks, and enterprise knowledge retrieval systems.
• Experience designing and implementing knowledge graph solutions and graph databases.
• Strong understanding of software engineering fundamentals, including system design, testing, security, observability, and version control.
• Ability to lead technical initiatives, influence architectural decisions, and collaborate effectively across business and technology teams.

Preferred Experience

• Real-time data processing and streaming technologies such as Kafka, Flink, or Kinesis.
• AI governance, Responsible AI, and model risk management frameworks.
• Enterprise-scale AI platform development and solution architecture.

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.