Designs and builds data platforms, tools, and solutions that enable the Bank to manage, secure, and extract value from its data, providing technical leadership across multiple teams.
Compensation
The base salary for this position is reflective of the range of salary levels for all roles within this pay grade across the U.S. Individual salaries within this range will vary based on factors such as role, relevant skillset, relevant experience, education and geographic location. In addition to the base salary, this role is eligible to participate in an incentive compensation plan, with any such payment based upon company, line of business and/or individual performance.
Responsibilities
Design, develop, and support scalable data solutions, APIs, tools, and processes
Work closely with IT application teams, Enterprise Architecture, infrastructure, information security, and LOB stakeholders
Act as a principal technical expert and trusted advisor
Conduct research and development on current trends and technologies
Build and maintain CI/CD pipelines and self-service deployment tools
Requirements
Bachelor's degree in Computer Science, Information Systems, or related field
Nice to have: modern data platforms
Nice to have: cloud-native architectures
Nice to have: data transformation technologies (Snowflake, dbt)
Nice to have: traditional data engineering tools (IBM DB2, IBM Information Server/DataStage)
Software Engineer II on the HMS Factory Team building and maintaining automated testing, log-analysis, and scenario-generation tools for the Hivemind Platform.
Compensation
Pay within range listed + Bonus + Benefits + Equity
Responsibilities
Develop, test, and maintain Python scripts and libraries used to analyze simulation data
Support the development of analysis tools that process simulation outputs
Help build and maintain automated test workflows and wrappers around HMS Forge
Assist with developing program-specific test adapters, configuration files, and automation utilities in Python and C++
Contribute to programmatic scenario-generation tools
Requirements
Master’s degree in Computer Science, Computer Engineering, Aerospace Engineering, Systems Engineering, or a related technical discipline
Nice to have: Python-based data-analysis workflows
Nice to have: continuous-integration systems
Nice to have: test frameworks such as pytest, unittest, GoogleTest, Robot Framework
Lead design, development, and deployment of advanced computer vision and machine learning solutions for industrial and manufacturing applications.
Responsibilities
Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
Define data quality standards and establish model performance metrics to ensure production readiness.
Requirements
Master's degree in Data Science, Computer Science, Physics, or related field
The AI Data Engineer will design, build, and maintain data foundations for foundational applications, advanced analytics, machine learning, Generative AI, and LLM applications. The role sits at the intersection of data engineering, AI platform development, and data governance.
Responsibilities
Design, develop, and maintain scalable data ingestion, transformation, and enrichment pipelines.
Assess, modernize, and migrate legacy data platforms and tools to AI-ready data infrastructures.
Lead initiatives to replace manual or siloed data workflows with automated, cloud-enabled solutions.
Design and execute migration strategies for data assets in legacy applications and on-premise environments.
Refactor and optimize existing ETL/ELT pipelines and data models.
Hands-on, backend-heavy engineering role focused on building a unified, large-scale machine learning platform that drives one-to-one offer, content, and channel decisions. Includes technical leadership, architecture design, and mentoring engineers.
Compensation
The typical pay range for this role is: $144,200.00 - $288,400.00
Responsibilities
Architect and build scalable, production-grade backend services (APIs, microservices, batch and streaming pipelines)
Design data contracts and interfaces between data engineering, model training, and production serving layers
Own the design of versioned, queryable feature stores and point-in-time lookup APIs
Design and optimize large-scale distributed computing workflows
Set and enforce engineering standards across the ML codebase (modular design, dependency management, code review, automated testing, CI/CD)
Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with cross-functional teams to understand data requirements and deliver scalable data solutions.
Monitor and troubleshoot data pipelines to ensure reliability and performance.
health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
Engineer II, Software - Factory - New Grad - 6217Newf7d8749a-72d6-407c-bf98-292ea630c73a · Washington, US
Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science TeamNewAmazon · Bellevue, US