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Machine learning engineer

PendoFull-time$100k - $255k*Herzliya, IsraelMar 19, 2024

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Team Description 

The Machine Learning Group at Pendo is dedicated to enhancing Pendo’s platform by delivering actionable insights and reliable predictions that our customers trust and value. Our team is highly committed to adopting good research and development practices while maintaining a keen understanding of the customer's perspective, ensuring that our solutions are technically robust and aligned with their needs.

Our solutions include diverse focus areas, from classical ML algorithms to cutting-edge generative models embedded in Pendo’s core product suite. By combining qualitative and quantitative data, we take projects from initial ideation to production, aiming to provide better and actionable insights to our customers.

As a member of our group, you'll collaborate closely with talented individuals, bringing together their diverse skill sets to solve complex problems and drive innovation. Our team culture is built on mutual respect, trust, and a genuine passion for our work. By joining our team, you'll contribute to developing state-of-the-art solutions that power Pendo and play a crucial role in shaping the company's future. At the Machine Learning Group, we emphasize valuing your expertise, nurturing your personal growth, and ensuring your impact is felt across the entire organization.

Role Responsibilities 

  • Design, develop, and maintain the engineering infrastructure that delivers our models based on MLOps best practices.
  • Work closely with the Data Scientists, Product Managers, and other stakeholders to define system requirements.
  • Take part in the productization effort of new ML products.
  • Collaborate with Pendo’s engineering organization (backend, frontend, and DevOps engineers) to establish robust interfaces and smooth integrations on ML deliverables.

Minimum Qualifications 

  • B.Sc. in Computer Science or equivalent.
  • At least one year of MLOps/Data/Backend engineering industry experience.
  • Experience with data-related tasks.
  • Production-grade Python coding experience

Preferred Qualifications 

  • Hands-on experience in delivering ML components to production at scale
  • Experienced with cloud technologies (Google Cloud/AWS/Azure)
  • Passionate about data and ML in general
  • Strong product thinking and a customer-first mindset

Pendo Description:

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers -- a simple way to understand and attack what truly drives product success.  Our mission is to improve society's experience with software.

Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech. You will gain experience in a diverse and exciting set of technologies and clients and have a real impact on Pendo's future. Our culture is passionate, dynamic, and fun.

EEOC

We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility

Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: [email protected]. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Compensation

Our salary ranges are based on paying competitively for our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide.

Individual pay rate decisions, including offers made within and over the expected salary range, are based on a number of factors, including qualifications for the role, experience level, skillset, and balancing internal equity relative to peers at the company.

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