Senior Machine Learning Engineer

Greenhouse

8d • $154,000 - $192,750 • Remote

About The Position

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 ai agents, 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.
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.

Requirements

• Degree or recent experience relating to Machine Learning
• Experience with NLP and large language models
• 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 librariesExperience designing and consuming APIs
• An ability to build consensus while creating space for othersExcellent prioritization and time management skills

Nice To Haves

• 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

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
• Develop applications that are compliant with our AI policies that prioritize privacy, security, ethical concerns, and best practices while handling data
• Contribute to and build all phases of the AI system lifecycle from ideation, model development, testing, evaluation, improvements and monitoring

Benefits

• Greenhouse provides a variety of benefits to employees, including medical, dental, and vision insurance, basic life insurance, mental health resources, financial wellness benefits, and a fully paid parental leave program.
• For US-based employees, we offer short-term and long-term disability coverage, a 401(k) plan and company match.
• U.S. based employees also receive, per calendar year, up to 14 scheduled paid holidays and up to 80 hours of paid sick leave.
• Non-exempt employees accrue up to 20-25 days of paid vacation time annually, depending on tenure, and exempt employees have flexible paid time off (PTO).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed