Remote Senior Machine Learning Engineer
Zuora
πRemote - India
Please let Zuora know you found this job on JobsCollider. Thanks! π
Job highlights
Summary
Join Zuora Platform tech as a core member of the AIMS team (AI, ML and science) to leverage the latest AI technologies to enable total monetization for Zuora. Opportunities lie across the suite of Zuora products and beyond.
Requirements
- 7+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience
- Strong data/ML engineering background, with experience in building and maintaining ETL pipelines, data modeling, data warehousing concepts, and familiarity with Big Data techniques to take models to production
- Curious mind to learn, explore and identify biggest customer opportunities
- Build strong relationships across both technical and business/product teams, earn trust with leadership
- Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay
- Willingness to dive deep into the tech stack as well as hands-on coding
- Experience in building end to end ML models, across the ML lifecycle
- Strong communication and leadership presence
- Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite
- Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments
- Bachelors/Masters in a technical or natural sciences domain from a top university
Responsibilities
- Identify $ opportunities - think big picture, work with product, tech and customer-facing teams to identify the largest customer problems that can be solved using ML
- Stakeholder relationships and strong communication - work closely with a wide variety of stakeholders to build cohesive plans and execute them
- Technical expertise, simplify complexity - build end to end ML models, be it classification/ unsupervised/ LLMs using a combination of structured and unstructured data
- End to end ownership, delivering results - Particular focus on the ML engineering aspect of the model building lifecycle is required
Benefits
- Competitive compensation
- Corporate bonus program and performance rewards
- Company equity
- Retirement programs
- Medical insurance
- Generous, flexible time off
- Paid holidays
- Wellness days
- 6 months fully paid parental leave
- Learning & Development stipend
- Opportunities to volunteer and give back, including charitable donation match
- Free resources and support for your mental wellbeing
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