Principal AI ML Engineer
Fidelity Investments is a privately held, Boston-headquartered financial services company providing investing, trading, retirement, wealth management, brokerage, workplace benefits, custody and clearing, and digital-asset services.
Maintainer signals as of 9/25/2026
About Fidelity Investments
Fidelity serves individual investors, employers, wealth-management firms, institutions, innovators, and charitable donors through diversified financial-services businesses. Current offerings include brokerage and trading, mutual funds and exchange-traded products, retirement and workplace savings, financial planning and advice, wealth management, institutional custody and clearing, and crypto/digital-asset products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will architect secure, scalable AI and machine-learning systems for training, inference, observability, and monitoring. You will build MLOps infrastructure, agentic workflows, AI-safety frameworks, and data pipelines; evaluate system performance; integrate governance; and mentor engineers on advanced ML and secure development practices.
Requirements
- Bachelor’s degree and five years of relevant experience, or a Master’s degree and three years of relevant experience
- Experience developing ML platform applications for cloud infrastructure using agile methodologies
- Experience with AWS, Azure, Google, IBM, Terraform, Kubeflow, IAM, KMS, Hadoop, MongoDB, PostgreSQL, Python, Java, Airflow, Jenkins, Git, MLflow, Go, FastAPI, SageMaker Clarify, CloudWatch, Datadog, Splunk, Streamlit, and Gradio
- Experience with adversarial robustness, federated learning, model governance, MLOps, CI/CD, RAG, vector databases, OpenSearch, Redis, and Memcached
- No immigration sponsorship
Responsibilities
- Architect AI and ML systems for training, inference, observability, and monitoring
- Develop secure and trustworthy AI frameworks
- Build agentic AI workflows for data pipelines and model lifecycle operations
- Prototype advanced AI and ML methodologies
- Evaluate performance, reliability, and robustness under production constraints
- Integrate AI safety and model assurance into enterprise architectures
- Integrate AI governance into enterprise architectures
- Mentor engineering teams on ML algorithms, infrastructure, and secure development
Benefits
- Fully paid parental leave
- On-site health and wellness centers