Senior Software Engineer, MLOps

Forward Financing
CA$175,000 - CA$220,000Remote

About The Position

Forward Financing is a financial technology company based in Boston, Massachusetts with team members throughout the United States, Dominican Republic, and Canada. The company is on a mission to unlock the capital that fuels small businesses across America. Recognized as a Best Place to Work by Built In Boston and certified as a Great Place To Work®, Forward is investing in its employees, technology, and customer experience – with long-term success in mind every step of the way. Forward Financing is a financial technology company headquartered in Boston, MA with an operational hub in the Dominican Republic, a satellite office in Salt Lake City, Utah and a growing team in Canada. Forward is on a mission to unlock the capital that fuels small businesses across America. Recognized as a Best Place to Work by Built In Boston and certified as a Great Place To Work®, Forward is investing in its employees, technology, and customer experience – with long-term success in mind every step of the way. Our Engineering team serves as a key driver of innovation at Forward Financing. We build the software that powers a FinTech product that serves Small Businesses across the country. A key part of our strategy involves leveraging data from dozens of sources to power our AI/ML initiatives and our analytical capabilities. We're looking for an experienced Senior Software Engineer to join our team, responsible for the systems that power our online (real-time) feature store — the infrastructure that serves ML features to production models with low latency and high reliability.

Requirements

  • 5+ years of software experience, with a focus on backend systems (Python required) and 2-3 years of MLOps experience
  • Strong experience with relational databases (Postgres preferred) — schema design, query optimization, and operating databases under production load
  • Experience building and operating real time inference systems
  • Understanding of the unique reliability and correctness demands of ML-serving infrastructure (data freshness, training/serving skew, feature consistency)
  • Experience in mutli-service architectures and design patterns
  • Experience in Agile software development
  • Typically has a Bachelor's degree in Computer Science, Data Engineering, or a related field, or additional relevant experience

Nice To Haves

  • Experience with feature stores (e.g., Feast, Tecton, SageMaker Feature Store) or building an equivalent system in-house
  • Experience with MLOps tooling (e.g., MLflow, Airflow, dbt) and ML model deployment/serving patterns
  • Experience designing and implementing complex systems across multiple software applications and/or languages
  • Excellent written and verbal communication
  • Ability to influence others
  • Demonstrated project management skills

Responsibilities

  • Design, build, and operate the online feature store — the real-time serving layer that delivers ML features to production models with low latency and strong consistency guarantees
  • Build and maintain data pipelines (batch and streaming) that compute, validate, and publish features from source systems into the online and offline stores
  • Work on the data models and Postgres schemas that back real-time feature serving, optimizing for query performance, freshness, and scale
  • Act as a technical leader for feature store infrastructure; help drive enhancements to quality, scalability, reliability, and observability for the systems ML models depend on
  • Partner closely with our Data Science, Analytics Engineering, Product Management, and Application Development teams to translate business requirements into production-grade engineering solutions
  • Contribute to mentoring for junior engineers
  • Contributing to best practices and raising the bar through thoughtful code reviews and contributions to technical design discussions

Benefits

  • medical
  • dental
  • vision
  • a flexible time-off policy
  • paid parental leave
  • RRSP match
  • wellness reimbursement
  • volunteering days
  • annual professional development budget
  • charitable donation match
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