Machine Learning Engineer

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

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

Own well-scoped ML components or models : You will take ownership of specific components, executing on defined problems with guidance

Train and deploy models using established patterns, and ship models to production following existing tooling and standards

Monitor and debug models with help from senior engineers, and work to improve model performance incrementally

Implement AI governance, privacy, and security requirements as defined

Collaborate within the team and with partner functions, while communicating progress, risks, and blockers clearly

You should have

Degree or recent experience relating to Machine Learning

Familiarity with 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

A strong grasp of Python

Experience training and experimenting with deep learning models as well as serving them in production

Experience with transformers and other HuggingFace libraries

Experience building 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! Your background has given you a unique perspective and set of transferable skills that aren't always in alignment with a given role - but those are qualities we value at Greenhouse. If you don't meet 100% of the qualifications outlined above, we still strongly encourage you to apply

Applicants must be legally eligible to work in Canada as of the start date chosen by the Company. We are unable to support sponsorship at this time.

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 $120,000 - $180,000 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.

The anticipated closing date for this role is February 20th, 2026.

Who we are

At Greenhouse, we live by our mission through using our own product to help us hire the right person for the job, every time. 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. We believe that bringing together a variety of perspectives makes us a stronger company – and we nurture leaders who create an inclusive culture and invest into employee resource groups that celebrate our differences and life experiences. We’re proud to have built an award-winning culture that’s been recognized as Fortune’s Best Places to Work and Inc.’s Best Workplaces multiple years in a row.

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 accommodations@greenhouse.io.

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.

Greenhouse has demonstrated its commitment to being : Respectful, Provides candidates with inclusive and positive experiences, Communicative, Sends timely application and interview updates, Prepared, Prepares interviewers to ask informed and consistent questions.

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