Overview
The Workplace Investing AI Delivery Engineering Chapter team is seeking a Principal Machine Learning Engineer to design, implement and improve technical solutions for AI model deployment, data pipelines, hosting, and API access. We are looking for a motivated technologist with a deep passion for data and application design to help build AWS based AI solutions to extract data from databases and unstructured data sources and harness AI algorithms to solve different types of use cases. This role will be a great mix of peer mentorship, technical leadership, application development, API development, data pipeline design, and hands-on work, in partnership with our data scientists and business teams.
Responsibilities
Design, build, and automate complex and customized data pipelines with multiple ingress sources and multiple consumers, including API-driven web applications.
Develop scalable microservices in Java/Spring Boot and/or Python; Angular experience is a plus.
Engineer data platforms on AWS with CI/CD pipelines, IAM roles and policies, Snowflake or RDS for analytics data hosting, EC2/EKS compute setup, and orchestration tools like Airflow. Demonstrate superior SQL skills and perform deep data analysis across multiple database platforms.
Work with AWS Machine Learning stack (SageMaker, Bedrock, Lambda, Step Functions, EC2/EKS, IAM, API Gateway, S3, RDS) and implement MLOps/GenAIOps practices including CI/CD pipelines, model hosting, monitoring, evaluation, observability, and automated deployment workflows.
Provide technical leadership with peer coaching and strong communication and presentation skills within collaborative teams to deliver high-quality data solutions.
Hands-on experience deploying machine learning models and ML Ops.
Qualifications
Deep experience (7+ years) designing, building, and automating complex data pipelines with multiple sources and consumers.
Significant API development experience building scalable microservices in Java/Spring Boot and/or Python; Angular experience is a plus.
7+ years of data engineering experience on AWS, including data manipulation, CI/CD deployment, IAM, cloud data platforms (Snowflake or RDS), and compute setup (EC2/EKS) with orchestration tools like Airflow.
2+ years of hands-on experience with AWS Machine Learning Stack (SageMaker, Bedrock, Lambda, Step Functions, EC2/EKS, IAM, API Gateway, S3, RDS) and MLOps/GenAIOps practices.
Strong technical leadership, peer coaching, and effective communication in collaborative environments.
Hands-on experience deploying ML models.
Bachelor’s Degree or equivalent experience.
The Team
The team is an agile squad in one of the Artificial Intelligence Product Areas in Workplace Services. The squad focuses on automating manual and error-prone processes using AI/ML and supports personalization use cases to help Fidelity customers. It uses cloud technologies and adheres to modern software engineering principles, offering opportunities to build innovative and high-value AI-powered solutions.
Company Overview
Fidelity is an equal opportunity employer committed to a diverse and inclusive workplace. For information about working at Fidelity, visit FidelityCareers.com.
Accommodation Language
Fidelity will reasonably accommodate applicants with disabilities who need adjustments to complete the application or interview process. Please email accommodations@fmr.com or call 800-835-5099, prompt 2, option 2 to request an accommodation.
Category
Information Technology
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