This listing doesn't post a salary. Most similar roles pay
$170,875–$243,425.
Based on 240 similar postings.
Employer
About Fidelity Financial Services
Fidelity Investments is one of the largest financial services companies in the world, offering brokerage services, mutual funds, retirement planning, wealth management, and life insurance to individuals and institutions. Industry: Financial Services & Investment Management
Fidelity Financial Services currently has
47 open roles
on FindRole.
Listed pay typically runs
$123,500–$185,000
across 10 roles with salary data.
As a Principal AI/ML Engineer, you will design and develop advanced machine learning systems and trustworthy AI frameworks to support large-scale enterprise platforms. You will build robust pipelines for model training, inference, and continuous monitoring while developing agentic workflows to automate data pipelines and MLOps infrastructure. Your work involves researching cutting-edge methodologies like federated learning, adversarial robustness, and multi-agent safety mechanisms to ensure high-assurance deployment across critical business functions. The role requires expertise in Python, Java, Go, and FastAPI, alongside tools such as SageMaker, Kubernetes, Terraform, Airflow, and Jenkins. You will utilize technologies including AWS Glue, Kinesis, DynamoDB, and PostgreSQL, while implementing RAG pipelines with vector databases and OpenSearch. Key technical focuses include infrastructure as code, container orchestration via Kubeflow, and high-performance serving using Triton and Deep Java Library.
Provide technical guidance and mentorship to engineering teams on advanced ML algorithms and secure development practices.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Information Technology, Information Systems, or a related field and five years of experience as a Principal AI/ML Engineer.
Master's degree in Computer Science, Engineering, Information Technology, Information Systems, or a related field and three years of experience as a Principal AI/ML Engineer.
Experience developing ML platform applications for cloud infrastructures (AWS, Azure, Google, or IBM) using agile methodologies.
Expertise in architecting scalable, secure, and distributed systems using Infrastructure as Code (Terraform) and container orchestration frameworks like Kubeflow.
Proficiency in big data tools (Glue, EMR, Kinesis, Athena, DynamoDB), ETL pipelines, and multi-agent systems.
Experience developing agentic workflows with frameworks such as Strands, CrewAI, LangGraph, or OpenAI Swarm.
Expertise in MLOps using Airflow, AWS Step Functions, Jenkins, Git, MLflow, and JFrog Artifactory.
Proficiency in Python, Java, Go, and FastAPI for building high-performance, multi-threaded, and asynchronous solutions.