Job description
Zipdev is seeking a ML/AI Applied Engineer to apply advanced machine learning models that predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cashflow, 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.
Key Technologies our client Use
- Backend: Go, Python.
- Cloud: Amazon Web Services (AWS).
- Data: MongoDB, PostgreSQL, S3, Sagemaker, Snowflake, Tableau.
- Front End: React, Typescript.
- Mobile: Flutter, Dart.
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.
Master’s degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
Relevant bachelor’s degree in a STEM field with 10+ years of relevant work experience in Machine Learning and Statistics.
Strong experience in AI and ML in the financial technology or service industry, including working with credit and financial datasets.
Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
Experience building ML models with PyTorch, Scikit-learn, and GenAI models.
Very strong knowledge of Python and SQL.
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.
Proven track record in building and deploying machine learning models, with a strong understanding of the theory and tradeoffs behind these techniques.
Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.
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.
Experience working with LLM frameworks such as HuggingFace libraries and with agent-based frameworks such as LangChain and Mirascope.
Familiarity with Snowflake for cloud data warehousing, data integration, and efficient handling of large-scale data storage and processing.
Above and Beyond
- PhD degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
- Experience in the FinTech or PropTech areas.
- Experience in a startup environment.
- Experience with microservices.
- Experience working with data governance policies in SOC2 or similarly certified organizations.
Our Recruitment Process
Video Interview
20-minute take-home skills test
30-minute Call with the Recruiter (project, benefits, etc.)
Interviews directly with the client (depending on the project the # of interviews may vary, this may include an assessment)
Final Offer
Work remotely Monday - Friday, 40 hours a week (no weekends)
Vacation: 10 business days a year
Holidays: 5 National Holidays a year
Company Holidays: 5 Company Holidays a year (Christmas Eve, Christmas Day, New Year’s Eve, New Year’s Day, Zipdev Day)
Parental Leave
Health Care Reimbursement
Active Lifestyle Reimbursement
Quarterly Home Office Reimbursement
Payroll Deduction Purchase Plans
Longevity Bonus
Continuous Learning Bonus
Access to Training and Professional Development Platforms
Did we mention it’s REMOTE?!!
One of our core values at Zipdev is “Be authentic.” that’s why we encourage you to answer the application form in your own words; we are interested in getting to know you, not a digital assistant.
Wondering how our remote environment or our payment method work? We’ve put together some helpful answers in our FAQs at the bottom our our career site. Take a look and let us know if you have any other questions!
