Senior Software Engineer (Python Development)

Senior Level Machine Learning EngineerAs a Machine Learning Engineer, you will build and maintain large scale ML Infrastructure and ML pipelines. Contribute to building advanced analytics, machine learning platform and tools to enable both prediction and optimization of models. Extend existing ML Platform and frameworks for scaling model training & deployment. Partner closely with various business & engineering teams to drive the adoption, integration of model outputs. This role is a critical element to using the power of Data Science in delivering Fidelity's promise of creating the best customer experiences in financial services.The RoleThe Expertise and Skills You BringBachelor's or Master's Degree in a technology related field (e.g. Engineering, Computer Science, etc.)8+ years of proven experience in implementing Big data solutions in data analytics space2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS SagemakerExtensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement requiredExperience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python's ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworksData movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologiesStrong knowledge of developing highly scalable distributed systems using Open-source technologiesExperience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)Solid experience in Agile methodologies (Kanban and SCRUM)Strong technical design and analysis skillsAbility to deal with ambiguity and work in fast paced environmentExperience supporting critical applicationsFamiliarity with applied data science methods, feature engineering and machine learning algorithmsData wrangling experience with structured, semi-structured and unstructured dataExperience building ML infrastructure, with an eye towards software engineeringExcellent communication skills, both through written and verbal channelsExcellent collaboration skills to work with multiple teams in the organizationAbility to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystemThe TeamPI Data Engineering team (part of Personal Investing Technology BU) is focused on delivery data and ML solutions for the organization. As part of this team, you will be responsible for building advanced analytics solutions using various cloud technologies and collaborating with Data Scientists to robustly scale up ML Models to large volumes in production.