Senior Machine Learning Engineer


We believe in the power of hiring. Because the potential for people to do something outstanding has everything to do with being in the right role, on the right team, at the right time. That’s where Greenhouse comes in – from recruiting to on-boarding, we make software to help every company be great at hiring.

Greenhouse is looking for a hands-on Senior Machine Learning Engineer to lead our Data Products team!

This team is responsible for developing machine learning models which will help enhance Greenhouse products like our resume parser, sourcing, and sales. In addition, in collaboration with the data science, product, and engineering teams, this team is also responsible for deploying, monitoring and maintaining those models.

You will own a good portion of the initial development process and help Greenhouse implement and grow the first Machine Learning team.

Who will love this job

  • A deep learning practitioner, who is eager to unlock the potential of deep learning for various applications
  • A generalist, who has the 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, who can work with multiple Greenhouse teams to find the best way to use data to provide value to Greenhouse customers and will do everything needed to make that happen

What you’ll do

  • Help grow a team of 3 machine learning engineers with a focus on mentorship
  • Develop software applications from scratch with a strong focus on machine learning
  • Train deep learning models (e.g. BigScience’s Bloom 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

You should have

  • Strong Python experience
  • Experience training and experimenting with deep learning models using PyTorch as well as serving them in production
  • An ability to build consensus while creating space for others
  • Excellent prioritization and time management skills
  • Prior experience speeding up and reducing GPU memory requirements for large deep learning models during training and inference, a plus
  • 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 with transformers and other HuggingFace libraries, 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.




Who we are

At Greenhouse, we celebrate having a diverse group of hardworking employees and it hasn’t gone unnoticed. We’ve won numerous awards including Inc. Magazine Best Workplace (2018-2022), Glassdoor #1 Best Place to Work, Forbes Cloud 100, Deloitte Technology Fast 500, Inc. 5000, Crain’s Best Places to Work NYC, Fortune’s Great Place to Work (2019 – 2022),  and Mogul’s Top 100 Workplaces for Diverse Representation (2022). We pride ourselves on fostering a collaborative culture throughout every step of a Greenhouse employee’s journey. From day one of our interview process to executive “Ask Me Anything” sessions, we consistently cultivate an inclusive environment.

For all our employees, we offer a full slate of benefits from competitive salaries, stock options, fully paid option(s) for health coverage (medical, dental and vision), disability coverage, employer paid life insurance, mental health resources, financial wellness benefits, and a fully paid parental leave program. For US-based employees, we offer flexible vacation and a 401(k) matching program. For Dublin-based employees, we offer 25 days’ vacation and an employer matching pension program.

Our success in making companies great at hiring depends on our ability to create a diverse, equitable and inclusive environment. To that end, we’re committed to attracting, developing, retaining and promoting a diverse workforce, and infusing DE&I throughout all of our internal practices. By ensuring that every Greenie is able to bring a diversity of talents to our work, we’re increasingly capable of living out our mission and providing real insight from our products to support our customers. We encourage people from underrepresented backgrounds and all walks of life to apply. Come grow with us at Greenhouse, where we’re building a team to face the world’s increasingly complex and diverse hiring needs.

Want to learn more about our interviewing process? Check out our interviewing at Greenhouse page

**We are a distributed company and do our best work where it works best for us – as individuals and as teams.  Our regional headquarters are based in New York (North America) and Dublin (Europe), but our employees are distributed across the US, Canada, and Ireland. **

Our Talent Acquisition (TA) team at Greenhouse has recently been notified of a phishing scam targeting candidates applying for our open roles. Scammers have been posing as hiring managers and recruiters in an effort to access candidates’ personal and financial information. Please note that any communication from our hiring teams at Greenhouse regarding a job opportunity will only be made by a Greenhouse employee with an email address. We would never ask you as part of our interview process to provide personal or financial information, including but not limited to your social security number, online account passwords, credit card numbers, passport information and other related banking information. If you believe you’ve been a victim of a phishing attack, please mark the communication as “spam” and alert us right away at [email protected].

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