Principal, AI/ML Engineer

Job Description: 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 help extract data from both 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 lots of hands-on work along with partnering with our data scientists and business. The Expertise and Skills You Bring Deep experience (7+ years) of designing, building, and automating complex and customized data pipelines with multiple ingress sources and multiple consumers including API driven user-facing web applications Significant experience (7+ years) API Development building scalable microservices in Java/Spring Boot and/or Python ; Angular experience is a plus. Deep Data Engineering (7+ years) experience using AWS for data manipulation: establishing CI/CD pipelines to deploy code and services to AWS, familiarity with IAM roles and policies, using cloud-based data platforms like Snowflake or RDS for analytics data hosting, EC2 and or EKS compute set-up and work orchestration tools like Airflow . Superior SQL skills and experience performing deep data analysis on multiple database platforms Solid (2+ years) experience with AWS Machine Learning Stack - SageMaker, Bedrock, Lambda, AWS Step Functions, EC2/EKS, IAM, API Gateway, S3, RDS. Experience with MLOps & GenAIOps - CI/CD pipelines, model hosting, monitoring, evaluation, observability, and automated deployment workflows. Proven track record as a technical leader with peer coaching and strong communications and presentation skills working on collaborative teams to deliver high quality data solutions. Hands on experience deploying machine learning models and ML Ops. 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 goal of the squad is to find opportunities to automate manual and error prone processes using AI and Machine Learning techniques. Squads also work on using AI and Machine Learning for personalization use cases to help Fidelity customers. The squad intends to use cloud technologies and deploy solutions using all current software engineering principles. It’s a great chance to work on an agile team to help build innovative and high business value AI powered solutions to improve the lives of Fidelity’s customers. Company Overview We are currently working in a hybrid model with some flexibility for remote working. However, Fidelity is gradually transitioning towards a full-time return to the office. We believe this will help strengthen our culture and enhance both the associate and customer experience. At present, this transition is expected from 2027 onwards, with no fixed timeline in place. At Fidelity, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want! We are a privately held company that places a high degree of value in creating and nurturing a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and inclusive workplace where we respect and value our associate for their unique perspectives and experiences. For information about working at Fidelity, visit FidelityCareers.com. Fidelity Investments is an equal opportunity employer. Accommodation Language Fidelity will reasonably accommodate applicants with disabilities who need adjustments to complete the application or interview process. Please email us at [email protected] or call 800-835-5099, prompt 2, option 2 if you would like to request an accommodation. Category: Information Technology