AI/ML Engineer

Job summary

Design, develop, and deploy end-to-end AI/ML solutions, including data ingestion, model training, and lifecycle management. Partner with business stakeholders to translate complex challenges into scalable, cloud-native AI-driven applications.

Job details

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. 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.

What you’ll do

Design, develop, and deploy end-to-end AI/ML solutions, including data ingestion, model training, and lifecycle management. Partner with business stakeholders to translate complex challenges into scalable, cloud-native AI-driven applications.

Requirements

Requires a Bachelor's degree in a technical field and at least 6 years of experience in Machine Learning or Software Engineering. Candidates must have hands-on experience with AWS, Python, and modern MLOps practices.

Listed skills

• Kubernetes · Preferred
• CI/CD · Preferred
• Docker · Preferred
• Machine learning · Preferred
• Amazon Web Services · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• AWS
• SageMaker
• Machine Learning
• Generative AI
• LLMs
• RAG
• Vector Databases
• MLOps
• CI/CD
• Docker
• Kubernetes
• Knowledge Graphs
• Data Engineering
• Software Engineering
• System Design
• Model Risk Management
• Influencing Skills
• AWS SageMaker
• Large Language Modeling
• Agentic AI
• Cloud-Native Computing
• Responsible AI
• Business Problems
• Pipelines
• AWS Kinesis
• Concept Drift Detection
• Vector Database
• MLOps (Machine Learning Operations)
• Generative Artificial Intelligence
• Influencing Without Authority
• Observability
• Platform Design And Development
• Knowledge Graph
• Advanced Analytics
• Data Lineage
• Technical Design
• Artificial Intelligence
• Amazon Web Services
• Service Innovation
• Containerization
• Decision Making
• Version Control
• Computer Science
• Corporate Services
• Data Discovery
• Extract Transform Load (ETL)
• Data Quality
• Governance
• Graph Database

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Machine Learning Engineer
• Software Developers
• Computer and Information Research Scientists

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