Staff AI/ML Applied Engineer

Democratize Access To Credit 

Together we will dismantle barriers to housing for working families by using data to eliminate the racial wealth gap. The ability to build credit from rental payments has the potential to give over 45 million renters with little to no credit a pathway into the financial system. Those individuals then stand to save over $200,000 in reduced lifetime interest payments, build home equity by qualifying for mortgages, and build wealth by passing job screening requirements.

The Engineering Team 

We are building a team of owners and changemakers. It is not enough to have the intention to do good –Esusu engineers translate intent into action and outcomes. We believe that lone heroes cannot accomplish our ambitious goals. Lasting change requires work by determined and collaborative individuals with a customer-first mindset. Our engineers aim to delight our customers and drive our business and team forward by leveraging their technical skills, empathetic curiosity, and teamwork.

Our back-end is microservice-based, hosted in AWS, and mainly written in Go. Our front end is based on React and written in Typescript. Our mobile apps are built using Flutter. Our data infrastructure is based on MongoDB, PostgreSQL, S3, Sagemaker, Snowflake, Talend, and mainly written in Python.

We are continuously innovating and always open to new solutions. Because Esusu is a financial services company, we are obsessive about every aspect of compliance and security. We embrace a DevOps environment where the team is responsible for the full spectrum of development, testing, deployment, and maintenance, including working with product and business operations teams to create customer-focused solutions. Even though we are 100% remote, Esusu’s culture is intensely collaborative.

The Opportunity

Esusu is seeking a ML Engineer to apply advanced machine learning models that predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors. This role will work closely with the Data Analytics and Data Engineering teams to ensure the models are trained on high-quality data and integrated into production systems. This role requires a high degree of collaboration with key managers, product owners, and other peers and cross-functional partners that rely, produce, and interact with the data domain across the organization (e.g., Data Engineers, Data Analysts, Backend Engineers, Marketing, Sales). The ML Engineer will focus on creating interpretable, accurate, and scalable predictive models utilizing datasets generated from our AWS and Snowflake environments. Additionally, you will translate model insights into actionable strategies that drive business decisions and financial inclusion. 

In addition to the technical responsibilities, you will coach and mentor your fellow data analysts and data engineers. You will ensure efficient delivery through effective planning, engaging with others, prioritizing, and developing, testing, and releasing your work. You will exhibit and foster Esusu’s culture and operating principles.

Core Competencies

• Superb programming, software and data development skills – You can independently devise and implement solutions to problems with minimal explanation needed.
• Strong communication skills – You can efficiently translate between technical and non-technical audiences and have strong writing skills.
• High standards – Your work is of the highest quality and you continue to raise the bar within your immediate team and our organization.
• Balance velocity with long-term goals – You balance thinking big with delivering the right thing in an agile and speedy manner. You are curious, flexible, and nimble in your approach and implementation.
• Heart of a teacher – You are a capable mentor and able to inspire and empower others on your team.
• Getting work done and driving excellence – You strive for excellence and prioritize delivering high-quality outcomes and projects..
• Adaptability – You thrive in an environment that changes quickly and is constantly presenting new challenges. 

Basic Qualifications

• Knowledge & Background: Master’s degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis. We will also consider candidates with a relevant bachelor’s degree in a STEM field with 10+ years of relevant work experience in Machine Learning and Statistics.
• AI & ML Experience: Very strong experience in AI and ML in the financial technology or service industry, including working with credit and financial datasets.
• AI & ML Engineering: Proven track record in building and deploying machine learning models, with a strong understanding of the theory and tradeoffs behind these techniques.
• AI Modeling: Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.
• Programming Languages: Very strong knowledge of Python and SQL.
• Cloud Expertise: Strong experience with AWS cloud services and tools, including AWS SageMaker for model development, training, and deployment, and AWS Bedrock for building and fine-tuning foundation models.
• AI & ML Platforms: Experience in working with model registry tools such as MLflow, SageMaker Model Registry, or other similar systems, to track, version, and manage machine learning models throughout their lifecycle.
• DataOp & MLOps: Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle. 
• ML Languages: Experience building ML models with PyTorch, Scikit-learn, and GenAI models.
• LLM Models: Experience working with LLM frameworks such as HuggingFace libraries and with agent-based frameworks such as LangChain and Mirascope.
• Data Experience:Familiarity with Snowflake for cloud data warehousing, data integration, and efficient handling of large-scale data storage and processing.

Above and Beyond

• Specialized Knowledge & Background: PhD degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
• FinTech/PropTech Expertise: Experience working in FinTech or PropTech sectors.
• Startup Experience: Familiarity with the dynamics of startup environments.
• Software Engineering Experience: Experience with microservices.
• Compliance Knowledge: Experience working in SOC2-certified, ISO-certified, or similar organizations.

Key Technologies We Use

• Backend: Go, Python.
• Cloud: Amazon Web Services (AWS).
• Data: MongoDB, PostgreSQL, S3, Sagemaker, Snowflake, Tableau.
• Front End: React, Typescript.
• Mobile: Flutter, Dart.

Benefits

• Competitive Salary – for Series B startup – $200,000 - $235,000 annually
• Significant equity package- $750,000-$1M in RSUs, which vest over four years with a 1 year cliff.
• Full Medical, Dental, and Vision Insurance
• 401K Plan
• Fitness/Gym Stipend
• Paid Parental Leave
• Remote Work Environment – 100% virtual
• Flexible PTO Policy
• Mission Driven Company – a strong and driven culture

This job is eligible only for the following states: California, Colorado, District of Columbia, Georgia, New York, Illinois, Washington