Senior Machine Learning Engineer
| Company | Fidelity National Information Services |
|---|---|
| Location | Bellevue, WA, USA |
| Salary | $136190 – $228790 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior |
Requirements
- At a minimum, a Bachelor’s in CS or equivalent education and either 2+ years of relevant professional experience or advanced degree such as a master’s or PhD.
- Experience leading projects from architectural design to production, while setting and maintaining high standards of technical excellence across your team.
- Effective communication and collaboration skills, and a history of collaborating effectively with your team and cross-functional stakeholders.
- Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
- Experience with data management, data, and build pipelines.
- Experience with building and deploying machine learning models.
- Experience with AWS, Snowflake, Databricks or similar technologies.
Responsibilities
- Understand business objectives, product requirements and develop ML algorithms that achieve them.
- Build Prototypes, and proof of concepts to determine feasibility, then drive data-based decisions.
- Run experiments to assess performance and improvements.
- Provide ideas and alternatives to drive a product/feature.
- Define data and feature validation strategies.
- Deploy models to production systems and operate them including monitoring and troubleshooting.
- Design, build, and manage the data pipelines and infrastructure that collect, store, and process large volumes of transactional and customer data from various sources.
- Develop, deploy, and scale machine learning models and applications in production and lower environments.
- Ensure data quality, security and availability for the data, notebooks, models, experiments, and applications.
- Integrate ML models with the SaaS platform and other services and tools, such as the model registry, feature store, data lake, and event streams.
- Collaborate with data scientists to develop and test machine learning models.
- Drive code reviews to ensure code quality, maintainability, and adherence to coding standards.
- Provide live on-call support by participating in the team on-call rotation and owning production issues from root cause analysis to resolution to future prevention.
- Partner with cross-functional teams (engineering, product, design, security, compliance etc.) to bring ideas to life.
- Build secure, robust, scalable, and performant systems for processing transactions and managing customer data.
Preferred Qualifications
- Typical qualifications for the role are 5+ years of relevant professional experience or a combination of work experience and advanced education.
- Deep expertise in at least one area of Machine Learning and AI.
- Experience with financial services data sources.
- Experience with MLflow and Feast or other Feature Stores is helpful.
- Proficiency in modern development frameworks and languages. (e.g., Java, Python, Go).
- Proven ability to self-direct your technical work and scope projects effectively.
- Experience leading and mentoring junior engineers.
- Excellent communication and collaboration skills to influence both technical and non-technical stakeholders.
- Experience with cloud platforms (AWS, Azure, GCP).
- Experience with version control systems (Git), and DevOps practices like continuous integration and continuous delivery (CI/CD).
- A strong understanding of security best practices for building enterprise applications.