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Principal Machine Learning Engineer

Figure CA San Francisco, California, United States

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$401k · Senior Full-time Posted over 3 years ago 5 min read

About Figure

Figure is transforming the trillion dollar financial services industry using blockchain technology.

In three short years, Figure has unveiled a series of fintech firsts using the Provenance blockchain for loan origination, equity management, private fund services, banking and payments sectors - bringing speed, efficiency and savings to both consumers and institutions. Today, Figure is one of less than a thousand companies considered a unicorn, globally.

Our mission requires us to have a creative, team-oriented, and supportive environment where everyone can do their absolute best. The team is composed of driven, innovative, collaborative, and curious people who love architecting ground-breaking technologies. We value individuals who bring an entrepreneurial mindset to every task and will embrace our culture of innovation.

Every day at Figure is a journey in continuous learning yet a daily focus on getting work done that makes a difference. Join a team of proven leaders who have already created billions of dollars in value in the FinTech space!

Forbes America’s Best Startup Employers

Forbes Top 50 Blockchain Companies

Figure Series D Announcement

About the Role

Each member of the Data Science team plays an integral part of what we are building at Figure. We rely on advanced techniques in machine learning, cloud platforms and big data to drive decisions across the organization. If you are interested in working with an impressive team of Data pros who collaborate and challenge each other, and want to solve interesting problems to propel the company’s growth, apply now!

In this role, you'll be embedded with a team of machine learning developers. You'll be expected to help conceive, code, and deploy machine learning models at scale using the latest industry tools. Important skills include machine learning workflow automation and ML Ops.

What You’ll get to do

Support Figure in building a machine learning platform to serve multiple lines of business and data science personas.
Work with data scientists to refine workflow automation and increase productivity.
Partner with data scientists to understand, implement, refine, and design machine learning and other algorithms.
Perform regular A/B tests, gather data, perform analyses, and draw conclusions about model performance.
Work cross-functionally with product managers, data scientists, engineers, and communicate results to peers and leaders.
Explore new technology to determine how they might connect with the customer benefits we wish to deliver.
Build tools to monitor data pipeline performance, data quality, and models in production.
Establish best practices with coding standards, workflows, tools, and product automation.
Review and maintain existing codebase (pipelines, models, algorithms), continue to improve existing tools and create new ones.
Build fundamentally sound, production-ready software and data products using modern development lifecycle methodologies: CI/CD, QA, and Agile Methodologies and deploy highly scalable software
Work as part of a data team working with mature data science products.
Integrate applications and platforms with cloud technologies (e.g., AWS and GCP)

What We Look For

BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
5+ years of experience and a passion for designing, analyzing, and deploying machine learning-based solutions.
Applied experience designing, building, and optimizing data pipelines, architectures, and data sets.
Good understanding of machine learning methods and statistics, including ML project lifecycle and associated challenges at each stage of development.
Knowledgeable about machine learning frameworks (e.g. PyTorch, Tensorflow, XGBoost, etc)
Expert-level knowledge of setup and use of data processing tools (e.g. Spark, Dask, etc) and distributed computing frameworks (e.g. Ray, Dask, etc)
Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance such as I/O and memory tuning.
Experience with GPU acceleration (i.e. CUDA and cuDNN)
Experience with tools like MLFlow, Airflow, Prefect, Docker, and Kubernetes is ideal.

Benefits and Perks

Competitive salary and growth opportunities
Company quarterly performance based bonus
Equity stock options package
Employer funded comprehensive health, vision, dental insurance and wellness program for employees and their dependents
Employer funded life and disability insurance coverage
Company HSA, FSA, Dependent Care, 401k, and commuter benefits
Up to 12 weeks paid family leave
In office, remote, and hybrid work location options
Home office and technology stipend for those working outside of a traditional office more than 75% of the time
Flexible time-off plan to empower employees to take the time off that they want and need
Continuing education reimbursement
Routine Team swag deliveries!

Depending on your residential location certain laws might regulate the way Figure manages applicant data. California Residents, please review our California Employee and Prospective Employee Privacy Notice for further information. By submitting your application, you are agreeing and acknowledging that you have read and understand the above notice.

Figure is unfortunately unable to provide sponsorship for this position. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

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Is Kubernetes high demand?

▼

Yes, Kubernetes is currently in high demand in the technology industry

Kubernetes is an open-source container orchestration platform that is widely used for deploying, scaling, and managing containerized applications

It provides a standardized way to manage and automate the deployment of containerized applications across multiple hosts and provides benefits such as reliability, scalability, and flexibility

As more and more organizations move towards containerized architectures, Kubernetes has become a critical component of their infrastructure

Kubernetes is used by companies of all sizes, from startups to large enterprises, and across various industries, including finance, healthcare, and e-commerce

According to various job market and salary surveys, Kubernetes-related skills are in high demand, and job positions related to Kubernetes are growing at a rapid pace

In fact, Kubernetes is often listed as one of the top skills that are in high demand by technology companies

Overall, Kubernetes is a highly sought-after skill in the technology industry, and it's likely to remain in high demand in the foreseeable future as more and more organizations adopt containerization and cloud-native architectures.

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