Senior Machine Learning Operations Engineer

Key Skills

Python Programming, C++, C Programming, SQL, AWS, Deep Learning, Docker, Kubernetes-K8s, Flask, Lambda, MLOps tools

Job Description

Best Egg is a consumer financial technology platform that aims to help people feel more confident about their everyday finances through a suite of products and resources. Our digital financial platform offers simple, accessible, and personalized financial solutions including personal loans, credit cards, and a financial health resource center.

Our culture and values are one of the core reasons why our customers keep returning to Best Egg. We are committed to championing a culture of inclusiveness and diversity of thought, and we focus on providing a safe, flexible, and collaborative work environment. Our associates are encouraged to engage in creative problem solving, and we promote opportunities for growth and enrichment across the organization.

If you are inspired by inspiring others, Best Egg is the place for you.

Best Egg celebrates diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we will grow.

At Best Egg we believe everybody should have the opportunity to enjoy life. As a fast growing fintech, we are on a mission to help our customers gain easy access to funds and reach their financial goals. Our Best Egg personal loan product has an impeccable record and stands out in the industry with its strong value proposition and overwhelmingly positive customer reviews.

Data is at the heart of everything we do. Join a Data Science team working at the cutting edge within our industry and constantly advancing our ML practice. Our Data Science team is dedicated to creating machine-learning models that power innovation and creative insights that pioneer new products and help our business reach the next level. We work on diverse projects across all business units within the company and have a direct engagement model between data scientists and business stakeholders.

Join a collaborative group of Data Scientists skilled in predictive analytics and help them to deploy and monitor real-time production-grade models in projects spanning the business from credit risk, direct marketing targeting, fraud operations, and many more! Enjoy the stability of a profitable, award winning fintech and challenge yourself with plenty of growth and upward mobility within a data rich environment. Be a part of a growing team using the latest tools and technologies to disrupt the industry and empower our customers to reach their financial goals.

Duties & Responsibilities

• A generalist responsible for end-to-end AI/ML architecture solutions; leading our AI/ML lifecycle capability which includes feature repository, model pipelines, model training, deployment, monitoring, and governance
• Improve, expand, and streamline our existing deployment pipelines to help support faster deployments, low response times, and near-perfect uptime. 
• Engage with core infrastructure around model training, model deployment, ongoing monitoring tools, container management, and much more.
• Leverage modern software engineering practices to deploy AI/ML solutions at scale and actively participate in the ideation, the design and the prototyping of AI/ML powered products
• Work cross-functionally and collaboratively to foster ML Ops and ML Engineering best practices across the organization to influence other leaders and challenge the status quo
• Keep the organization up to date on the best in class MLOps technologies
• Enjoy a culture rich in learning and frequent small wins, our Data Science team is small but mighty and contributes insights to decisions made across the entire business. 

Requirements

• At least five years of professional engineering experience or work program equivalents in a relevant field
• Experience in operationalization of Data Science projects (MLOps) on AWS required – with specific experience with CodePipelines, Lambda, Step Functions, EventBridge, and Sagemaker a plus
• Production experience w/ Python & associated API frameworks (e.g. Flask, FastAPI)
• Experience with Kubernetes/Docker or other container orchestration tools in a production setting
• Experience managing an automated, E2E ML lifecycle through CI/CD best practices
• Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit
• Ability to utilize software engineering best practices, like maintainable code and testing libraries
• Experience with (near) real time feature processing/engineering, model tuning, and adaptive AI/ML pipelines a plus
• Experience with ML Feature Repository architectures a plus
• Exposure to machine learning fundamentals such as training data, models, and metrics
• At least one AWS certification in a relevant area
• Foundational knowledge of statistics and previous Data Science/Deep Learning experience a plus
• At least one of Scala, C/C++, similar is a plus
• Ability to work in a fast-paced environment and strong technical communication skills
• Enjoy a culture rich in direct communication, no politics, and continual learning - where we celebrate success and have fun too