Customer Success Engineers are technical points of contact for JetBrains customers, ensuring products meet enterprise users’ needs and driving adoption and expansion.
Locations (2)
Marlton, New Jersey, United States
United States
Compensation
$100,000—$200,000 USD
Responsibilities
Work closely with JetBrains Account Executives
Help customers adopt JetBrains products and services
Manage technical relationships for a portfolio of accounts
Develop and evaluate machine‑learning models for borrower repayment behavior
Apply causal inference and experimentation to measure intervention impact
Translate model predictions into decision algorithms
Partner with Product, Engineering, and Operations on payment experiences and collections strategy
Identify machine‑learning opportunities in servicing areas
Requirements
Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field
Nice to have: PhD in a quantitative field
Program Manager III, NPI Operations, Machine Learning
Drive technical outcomes by managing and resolving complex enterprise customer billing escalations through advanced diagnosis, analysis, and troubleshooting expertise.
Drive technical outcomes by managing and resolving complex enterprise customer billing escalations through advanced diagnosis, analysis, and troubleshooting expertise.
Contribute to relationship management across several projects and stakeholders as a key technical contributor, providing technical solution strategy to business, account management, and enterprise customers.
Uncover trends in customer issues and business objectives, and proactively create innovative solutions to address them in partnership with Product and Developing teams.
Influence product direction and advocate for customer needs by translating complex technical challenges into actionable strategies for cross-functional teams like Product Management and Software Developers.
Develop an in-depth understanding of underlying architectures to determine root causes, and write code to build customized technical solutions and internal tools that scale diagnostic capabilities globally.
Requirements
Bachelor's degree in Engineering, Computer Science, a related technical field, or equivalent practical experience
Nice to have: cloud technologies
Senior Technical Program Manager, GenAI Transformation
Lead GenAI Transformation Programs within Google Cloud Business Platform, driving strategy, technical execution, and operational governance of AI initiatives.
The Ads Safety team builds core infrastructure, developer tooling, and automated safety guardrails for the ML/LLM classifier's lifecycle to ensure Google Ads products and networks are safe and compliant.
Write and test product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Requirements
Bachelor’s degree or equivalent practical experience
Master's degree or PhD in Computer Science or a related technical field
Lead failure analysis and hardware resiliency for Azure cloud infrastructure, driving detection, prediction, and repair of hardware failures across millions of servers.
Compensation
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Lead failure analysis across server components
Define signals, thresholds, diagnostics and repair recipes
Improve isolation accuracy for repairs
Partner with software engineers and data scientists on detection rules
Leverage AI-powered tools and data-driven insights
Principal Product Manager to identify and build the next generation of content products and reusable intelligence systems, focusing on AI-native products and personalized intelligence for enterprise workers.
Compensation
The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Responsibilities
Own the vision and strategy for new content intelligence products, identifying unmet customer needs and technology shifts.
Build enterprise content intelligence as the first product focus, including personalized company and industry briefings, watchlists, and experiences.
Translate capabilities across user understanding, knowledge graphs, content agents, ranking, quality, and interactive components into coherent, reusable product systems.
Lead rapid customer discovery, prototyping, and experimentation to find product-market fit.
Partner deeply with design, engineering, applied science, editorial, and canvas product teams to integrate new products into Edge, Windows, MSN, and Copilot.
Requirements
Bachelor's Degree
Nice to have: 15+ years experience in product management
Research Interns put inquiry and theory into practice, collaborating with researchers and contributing to AI agent development.
Compensation
The base pay range for this internship is USD $6,810 - $13,480 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,920 - $14,610 per month.
Responsibilities
Conduct research and author peer‑reviewed publications
Build and prototype AI agent systems
Evaluate and improve agent performance
Collaborate across research and product teams
Present findings and contribute to community life
Requirements
Doctorate Degree program in Computer Science, Software Engineering, Electrical Engineering, or related STEM field
Nice to have: At least 1 year of research experience
Nice to have: Publications in top venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, COLM, AAAI, IJCAI, KDD, or SIGIR
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