Senior AI/ML Engineer

Fidelity Investments - Merrimack, NH

Full-time - Senior

Merrimack, NH

Securities, Commodity Contracts, and Other Financial Investments and Related Activities

About the position

As a Senior AI/ML Engineer in the Fidelity Fund & Investment Operations (FFIO) Advanced Analytics team, you will play a pivotal role in transforming manual business processes into efficient, automated solutions using cutting-edge AI and machine learning techniques. Your primary responsibility will be to collaborate closely with business product leaders and various teams to identify opportunities for improvement through AI/ML. This involves evaluating existing processes, identifying use cases, and exploring a range of AI/ML modeling techniques to design and deliver high-value solutions that enhance operational efficiency. In this role, you will leverage your extensive experience in data science to assess project scopes, define technical designs, and establish data requirements. You will independently develop and deliver AI/ML solutions, utilizing your strong programming skills in Python and familiarity with frameworks such as Django, Streamlit, and Pyspark. Your expertise in the AWS ecosystem, particularly with services like EC2, EKS, and Sagemaker, will be crucial as you work on deploying scalable solutions. You will also be responsible for conducting exploratory data analysis, data cleaning, and preparation, ensuring that the data is ready for modeling. Your knowledge of data warehousing concepts and SQL scripting will enable you to develop efficient data access processes from RDBMS databases, particularly on platforms like Snowflake and S3. You will design and develop machine learning pipelines, evaluate models, and validate their performance, employing various algorithms including NLP, supervised and unsupervised learning techniques such as decision trees, isolation forests, autoencoders, and clustering methods. As part of a dynamic team, you will contribute to the development of models that can handle both structured and unstructured data, and you will stay abreast of the latest advancements in AI and machine learning to drive innovation within the organization. Your excellent communication and presentation skills will be essential as you share insights and findings with stakeholders, ensuring that the solutions you develop align with business objectives and enhance operational excellence.

Responsibilities

• Collaborate with business product leaders to evaluate and improve manual business processes using AI and ML techniques.
• Identify use cases for AI/ML applications within the organization.
• Explore various AI/ML modeling techniques to design and deliver solutions.
• Assess project scope and define technical designs for AI/ML projects.
• Develop and deliver AI/ML solutions independently.
• Conduct exploratory data analysis, data cleaning, and data preparation.
• Design and develop machine learning pipelines and workflows.
• Evaluate and validate machine learning models.
• Develop models using NLP and various supervised and unsupervised ML algorithms.
• Work with both structured and unstructured data.

Requirements

• 5+ years of prior work experience as a data scientist or data analyst.
• Strong experience working with Python and familiarity with Django, Streamlit, and Pyspark.
• Experience working in the AWS ecosystem, particularly with EC2, EKS, and Sagemaker.
• Ability to assess project scope, technical design, and define data requirements.
• Conversant with data to perform exploratory analysis, data cleaning, and preparation.
• Knowledge of warehousing concepts and SQL scripting, especially with Snowflake and S3.
• Experience in designing and developing ML pipelines and model evaluation.
• Familiarity with NLP and various ML algorithms such as decision trees, isolation forests, and neural networks.
• Excellent verbal and written communication and presentation skills.

Nice-to-haves

• Experience with Gen AI / LLM models and prompt engineering.
• Familiarity with additional programming languages or frameworks related to data science.