Senior Machine Learning Engineer

Summary

Join Greenhouse as a Senior Machine Learning Engineer and develop machine learning models to enhance Greenhouse products such as resume parsing, anonymization, hiring, sourcing, and predictive analytics. Collaborate with data science, product, and engineering teams to deploy, monitor, and maintain these models. As a deep learning practitioner and generalist, you will leverage your expertise in PyTorch and Transformers to train deep learning models, deploy applications in production using AWS, and partner with the R&D team. You will also contribute to setting the vision and strategy for AI within the product suite. This role requires experience deploying, monitoring, and improving ML models, strong Python skills, and experience with transformers and HuggingFace libraries. Greenhouse offers a remote-first work environment, performance review programs, bonus structures, and an award-winning culture.

Requirements

• 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
• Applicants must be legally eligible to work in Canada as of the start date chosen by the Company

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• 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
• We are a remote-first company and have shared office spaces in New York City and Ireland, and optional co-working spaces that give us flexibility to do our best work anywhere
• We take an active role in our growth through a performance review program that’s committed to providing actionable feedback, and a bonus structure that rewards great performance