Senior Machine Learning Engineer

Greenhouse • Unknown, Canada • 4d ago

Our mission at Greenhouse is to make every company great at hiring – so we go to great lengths to hire great people because we believe that they’re the foundation of our success. At Greenhouse, you’ll join a team that collaborates purposefully, fosters inclusivity, and communicates with transparency and accountability so we can help companies measurably improve the way they hire. Join us to do the best work of your career, solving meaningful problems with remarkable teams. Greenhouse is looking for a Senior Machine Learning Engineer to join our team! In this role, you'll work with our team to develop machine learning models that enhance Greenhouse products like resume parsing/anonymization, hiring, sourcing, and predictive analytics. Additionally, we serve to support other product engineering teams on their journey of implementing more machine learning capabilities. You'll collaborate with data science, product, and engineering teams to deploy, monitor, and maintain these models, allowing you to refine your skills and contribute to key projects.

Who will love this job A Deep Learning practitioner - you are eager to unlock the potential of deep learning for various applications A generalist - you have experience and the ability to perform a wide variety of software engineering tasks, which are necessary to develop, deploy, and monitor a new software application. You have experience working on whole applications mainly in Python but welcome the opportunity to use Ruby or Typescript as needed. A collaborator - you are able to work with multiple teams to find the best way to use data to provide value to customers and will do everything needed to make that happen An entrepreneur - someone whose values align with our vision on how A.I. can assist in the hiring process.

What you’ll do Develop software applications with a strong focus on machine learning Train deep learning models using PyTorch and Transformers and experiment with (new) techniques to reduce their memory footprint, speed them up, or increase their accuracy Deploy software applications, including deep learning models, in production, using AWS and Greenhouse’s internal tools Partner with other members of the R&D team to uplevel their comfort and familiarity with shipping Machine Learning features Help set vision and strategy for AI within our product suite

You should have Experience deploying, monitoring, and improving ML models at a technology company Strong Python experience Experience training and experimenting with deep learning models as well as serving them in production Experience with transformers and other HuggingFace libraries Experience designing and consuming APIs An ability to build consensus while creating space for others Excellent prioritization and time management skills Experience with NLP and large language models, a plus Experience with machine learning models which are not deep learning (e.g. decision trees), a plus Experience using Docker and AWS (SageMaker endpoints, SageMaker notebooks, S3, IAM, …), a plus Your own unique talents! If you don’t meet 100% of the qualifications outlined above, tell us why you’d be a great fit for this role in your cover letter Applicants must be legally eligible to work in Canada as of the start date chosen by the Company. For purposes of processing or administering your employment relationship, personal information that you provide to the Company may be transferred to and accessed by an affiliate in the United States or elsewhere, or to agents and contractors (such as payroll companies, insurance companies, information technology consultants, etc.) that provide services to the Company. The national pay range for this role is $142,700 - $214,100 CAD. Individual compensation will be commensurate with the candidate's experience and qualifications. Certain roles may be eligible for additional compensation, including stock option awards, bonuses, and merit increases. Additionally, certain roles have the opportunity to receive sales commissions that are based on the terms of the sales commission plan applicable to the role.