Machine Learning Engineer

Kunai is a fast-growing digital agency of 120+ people specializing in fintech. Our fully remote team is driven by innovation and experimentation. Over the past decade, we've shipped over 150 products for clients that include Visa, the United Nations, Wells Fargo, Ernst & Young, and TOMS Shoes. Our founders built a previous agency (Monsoon) that was acquired by Capital One in 2015. As a Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. 
Engineering
Job Type
Full-Time (Remote)
Location
New York, NY (Remote)
Company
Kunai
https://jobs.lever.co/kunai/82c3559d-b9b2-47f2-b23c-aff46fa208df/apply
What you'll do:
  • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Retrain, maintain, and monitor models in production.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Use programming languages like Python, Scala, or Java.
  • What you'll do:
  • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:
  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Retrain, maintain, and monitor models in production.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Use programming languages like Python, Scala, or Java.
  • Preferred Qualifications:
  • 1+ years of experience building, scaling, and optimizing ML systems
  • 1+ years of experience with data gathering and preparation for ML models
  • 2+ years of experience developing performant, resilient, and maintainable code
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
  • 3+ years of experience with distributed file systems or multi-node database paradigms
  • Contributed to open source ML software
  • Authored/co-authored a paper on a ML technique, model, or proof of concept
  • 3+ years of experience building production-ready data pipelines that feed ML models
  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
  • Benefits

    We Remote

    Kunai is a fully remote company. If you have the skills, you can live and work anywhere you'd like.

    Flexible Hours & Vacation Time

    We expect a level of personal responsibility and leave you to figure out what suits you and your team.

    Learning and Development

    Kunai understands that constant learning is the only way to stay on top of your craft.

    Health, Dental, Vision

    Kunai provides full benefits and our plans offer a range of options.

    Maternal and Paternal Leave

    For our growing Kunai family!

    Career Coaching

    We want to help you reach your professional goals.