<h3>📋 Description</h3> • 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.
• Join us to do the best work of your career, solving meaningful problems with remarkable teams.
• 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.
• 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.
• 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.
• An entrepreneur - someone whose values align with our vision on how A.I. can assist in the hiring process. <h3>🎯 Requirements</h3> • Degree or recent experience relating to Machine Learning
• Experience implementing safe, ethical, and compliant ML systems (familiarity with ISO 42001/NIST AI RMF and the associated common controls)
• 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. <h3>🏖️ Benefits</h3> • 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.
• Greenhouse Software is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances.
• If you need assistance and/or a reasonable accommodation during the application process, reach out to
[email protected].
• Emails about job opportunities at Greenhouse Software are only offered by employees with @greenhouse.io email addresses. See this page on our website if you suspect a phishing scam.