Senior Research Scientist jobs at Mongodb in United States, Palo Alto

This role is a cornerstone of our Global VIP Support function, responsible for proactive, high-touch (“white-glove”) technology support for our most senior leaders and their Executive Assistants (EAs).

As the West Coast VIP Support Ambassador, you are the single-threaded owner for executive technology needs in the US Pacific time zone, partnering closely with our NYC (US/Eastern) and Dublin (EMEA) VIP specialists to deliver near 24×5 global coverage.

You will blend senior-level IT support with strong AV and collaboration expertise to protect the most critical executive workflows and events. You will also play a key role in developing and delivering IT training for the EA community, and partnering with Internal Comms and AV on All Hands support. This role requires excellent judgment, calm under pressure, empathy, and the ability to drive complex issues to resolution while maintaining executive trust.

1. White-Glove Incident Response & Resolution

• End-to-end ownership of VIP incidents (P0–P3) during West Coast core hours (typically 9:00–18:00 PT).
• Triage, diagnose, and resolve issues across devices, apps, networking, conferencing, and AV
• Own communication, status updates, and follow-through until full resolution
• P0/P1 live support:
• Join meetings live for shadow checks, audio/video verification, and real-time triage
• Rapidly implement workarounds (room swaps, dial-in bridges, alternate devices) when needed
• PagerDuty participation:
• Participate in the global VIP on-call rotation for after-hours/weekend executive incidents
• Acknowledge and route alerts, escalate per the VIP escalation matrix, and coordinate with NYC/EMEA counterparts
• Smart handoffs for non-VIP traffic:
• Quickly identify non-VIP/general tickets, capture clear diagnostic notes, and hand off to regional L2/IT support
• Remain the escalation point when the issue has executive impact

2. Proactive Care, Stability, & Event / All Hands Support

• Device health and stability:
• Perform regular health checks on executive laptops, backup devices, mobile devices, and conferencing apps
• Ensure OS, security tooling, collaboration apps, and certificates are up to date prior to key events or travel
• High-stakes events & All Hands support:
• Own technical prep for West Coast-based Board meetings, earnings calls, All Hands, customer keynotes, and other VIP events
• Partner with Internal Comms on All Hands execution, including:
• Slide advancement and content playback
• Run-of-show adherence and timing
• Panelist confirmation, speaker tech checks, and backup plans
• Partner with the AV team to provide backstage live support, including green room coordination, backstage comms, and rapid issue triage during broadcasts
• AV/room expertise:
• Maintain a deep understanding of executive rooms and spaces (Zoom Rooms, Teams rooms, DSPs, control systems, cameras, mics)
• Partner with AV Engineering to quickly remediate recurring room issues and ensure executive spaces meet reliability targets
• Automation mindset:
• Identify repeatable VIP support workflows and collaborate with IT/AV engineering to automate (e.g., monitoring alerts, health checks, loaner kit workflows, report generation)

3. Executive Relationship Management, EA Training & Travel Support

• Single-threaded owner for a portfolio of executives/EAs:
• Build trusted relationships with executives and their EAs as their direct technology partner
• Conduct regular check-ins to understand pain points, preferences, upcoming travel, and event calendars
• EA IT training & enablement:
• Design and deliver IT training and development programs for the EA team, focused on collaboration tools, meeting best practices, AV room usage, and VIP playbooks
• Create short guides, office hours, and targeted sessions to help EAs execute complex events and day-to-day workflows with less friction
• Travel & remote support:
• Prepare travel briefs (devices, adapters, connectivity, security, backup options) for executive trips
• Coordinate with hotels, venues, and customer sites on AV and network readiness when required
• Provide occasional on-site support at home offices or offsite locations as needed
• Documentation & knowledge sharing:
• Keep VIP runbooks, playbooks, and checklists current for core tools (Zoom, Teams, WebEx if used, room systems, travel setups)
• Contribute to internal knowledge bases to reduce repeat incidents and enable broader IT teams and EAs to support executives effectively

0–30 Days: Foundational Readiness & Onboarding

• Fully up to speed on the services and technologies we deploy and maintain
• Successfully passed a mock P0 drill, demonstrating calm under pressure and ability to use communication templates
• Complete full runbook, PagerDuty, and Zendesk workflow training
• Shadow two full on-call rotations before taking primary ownership

30–90 Days: Independent Ownership & Proactive Action

• Independently handle day-to-day VIP IT tasks and manage regional handoffs at shift end
• Actively initiate monthly VIP device health checks for assigned executive portfolios
• Fully own triage and resolution for VIP P0/P1 incidents within assigned SLAs (e.g., P0 First Response < 15 min; P1 First Response < 30 min)
• Begin actively developing novel solutions to inefficient processes and problems in your region

90 Days – 1 Year: Efficiency, Strategy & Process Ownership

• Achieve and consistently maintain high weekend SLA compliance (>98%) for PagerDuty coverage
• Lead quarterly EA roundtable/account reviews for your assigned executive portfolio
• Drive a measurable decrease month-over-month in repeat incidents by owning and implementing preventative actions
• Think largely in terms of efficiency, using the skills necessary to execute on automation ideas, and become a trusted technical voice in the organization

Required

• Experience:
• 5+ years in IT end-user support, service desk, or field support
• Meaningful experience (ideally 2+ years) supporting senior leaders, high-touch stakeholders, or VIP users
• Platform & tooling fluency:
• Strong experience with macOS and Windows, common productivity suites (Google Workspace and/or Microsoft 365), and modern endpoint management
• Troubleshooting strength:
• Proven ability to troubleshoot complex, end-to-end issues across devices, networks, identity, and collaboration tools
• Comfortable working in ambiguous, time-sensitive situations and making practical tradeoffs
• Collaboration, AV & live events:
• Hands-on experience with video conferencing platforms (Zoom, Zoom Rooms, Teams, etc.) and meeting room systems
• Experience supporting live events or All Hands (e.g., slide advancement, panelist support, run-of-show execution)
• Familiarity with common AV components (cameras, microphones, DSPs, control panels) and how they interact in a room
• Training & communication:
• Exceptional written and verbal communication skills
• Experience explaining workflows, tools, or best practices to non-technical users, and adapting training material for an EA audience
• Customer mindset:
• Empathetic, patient, and service-oriented; comfortable supporting demanding schedules and high expectations
• Discreet and trustworthy with sensitive information

Preferred

• Experience in a high-growth SaaS, technology, or financial environment supporting senior leadership
• Familiarity with tools such as Okta, JAMF, Meraki, Confluence, Jira, Slack, and modern monitoring/alerting systems (e.g., PagerDuty, Utelogy, Zoom dashboards)
• Experience partnering with AV Engineering, Workplace/Facilities, and Internal Comms teams to deliver high-quality live events and All Hands
• Comfort with light automation or scripting (e.g., Python, PowerShell, or workflow tools) to reduce repetitive manual tasks

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment
• Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

• Experience integrating infrastructure with production ML workloads
• Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
• Contributions to open-source infrastructure for ML serving or search

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence

This role can be based out of our Palo Alto office, or remotely in the United States.

• Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers
• Innovate in next-generation information retrieval and LLM agent paradigm
• Collaborate closely with other research scientists and research engineers as well as peers across the organization

• PhD degree in Computer Science or related field
• A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues
• Strong background in machine learning, deep learning, and natural language processing
• Experience building complex neural networks for language and visual understanding
• Capable of conducting rigorous empirical studies to validate theoretical results
• Excellent leadership, problem-solving, and communication skills

• Opportunity to work on real-world problems at the cutting edge of AI research
• Opportunity to utilize research vision to innovate the entire company and make real-world impact
• Exposure to the full lifecycle of AI model development, from research to production
• Our compensation (base + equity) for this position is competitive with frontier AI labs

• Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers.
• Innovate in next-generation information retrieval and LLM agent paradigm.
• Collaborate closely with other research scientists and research engineers as well as peers across the organization.

• PhD degree in Computer Science or related field
• Strong background in machine learning, deep learning, and natural language processing
• Familiarity with training distributed training of neural networks for language and visual understanding

• Opportunity to work on real-world problems at the cutting edge of AI research
• Opportunity to utilize research vision to innovate the entire company and make real-world impact
• Exposure to the full lifecycle of AI model development, from research to production
• Our compensation (base + equity) for this position is competitive with frontier AI labs

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment.Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

• Experience integrating infrastructure with production ML workloads
  Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
  Contributions to open-source infrastructure for ML serving or search

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence

• 9+ years experience working in a Customer Success, Account Management, Client Services or other similarly customer-centric role
• A background and passion for advocating on behalf of your customers - this role should act as an extension of our customers team within MongoDB
• A mind for technology - we’ll teach you about MongoDB and databases, but our customers and product are inherently technical and you should have an aptitude and curiosity to learn about those concepts
• The ability to act with a high level of autonomy, you will be expected to take full ownership of your customer portfolio and make key decisions to drive effective customer outcomes; including deciding when to include our executive team or c-suite in customer escalations, how to de-risk or de-escalate customer issues and conflict and advocating to internal teams including sales, professional services, etc
• An entrepreneurial mindset - this is a new team at MongoDB where you will be required to both deviate from established procedure and often build entirely new process or practices to ensure we best serve this customer segment
• Team player and passion for collaboration - this role will work with some of our most strategic growth customers so must align closely to Sales, Professional Services, Tech Services, and the broader MDB ecosystem
• Prior exposure to database, cloud, and infrastructure technology is a plus
• German speaking

• Work as a strategic advisor to your customer providing them with guidance on MongoDB best practices and their overall technology strategy; this could include running enablement sessions alone or with another internal MongoDB team members, advising the customer on strategies to optimize their technical environment or current spend with MongoDB, positioning and recommending product features and best practices to accelerate customers time to value and growth
• Collect feedback and identify roadblocks from customers to inform internal teams including Product, Professional Services, and Leadership on how MongoDB can build a stronger product and go to market organization
• Act as the link between our customers and product engineering to develop new innovative solutions. You will be key in building the future roadmap of our product by acting as the Product team’s eyes and ears in this field
• De-escalate and resolve critical customer issues and complaints by finding the best possible solution for both the customer and MongoDB; this could include anything from navigating a customer outage that has a financial impact on their business, to helping an application team devise a custom MongoDB solution or implementation for their critical application, no day is the same
• Build and execute account plans to mitigate risk and drive growth 3+ quarters out across your portfolio
• Lead in-person executive business reviews for strategic customers in your portfolio, including interfacing with C-suite executives and other technical leaders to align to business objectives and agree to a mutual success plan
• Work on strategic internal projects to help build the Customer Success program; our expectation is that anyone in this role has strong business acumen and the ability to create and teach best practices, new process, and enablement to the broader organization
• Document all customer interactions in internal systems, including Gainsight and Salesforce.com
• Provide feedback and guidance to leadership on key signals within MongoDB Atlas that indicate healthy or unhealthy customer accounts; as our product evolves, we’ll need to be constantly adjusting our engagement strategies based on these signals, which you’ll be in the best position to identify and share back with internal teams
• Manage the relationship with Sales Leadership and Account Executives in your territory, including reporting on business performance, training on best practices, and rolling out program updates to ensure sales people and leaders are abreast of best practices for interacting with Customer Success
• Forecast expected churn and growth to your senior leadership team
• Help interview, onboard and ramp new team members - as a more senior team member you will have an immediate role in who joins the team
• Act as a leader amongst your peers, running enablement sessions, product certifications and being vocal in team meetings to ensure those around you grow

This role can be based out of our NYC office or remotely from anywhere in North America.

• Minimum 12 years of experience in programming, debugging, and performance tuning distributed and/or highly concurrent C/C++ software systems
• Strong systems fundamentals, including multi-threaded programming, performance profiling, and expert-level network programming
• Familiarity with database internals or building core components for data processing systems
• Familiarity with observability ecosystem and best practice
• Excellent verbal and written technical communication skills and a strong desire to collaborate with colleagues and mentor engineers
• Excellent time and project management skills including the ability to make realistic assessments of project cost and complexity

• Lead the architecture and implementation of low-level networking components that drive the performance, scalability, cost-efficiency, and resiliency of MongoDB Server
• Design and implement observability improvements that enable MongoDB engineers and customers to quickly and accurately diagnose the root cause of production issues
• Handle networking-related customer escalations from Technical Support team and coach teammates to do the same
• Write production-ready database code in C++, improve the existing code, and mentor their team to write higher quality code
• Own all code the Networking & Observability Team maintains, ensuring it achieves a high standard for quality (including security, durability, availability, and performance) and maintainability
• Write and improve unit and integration tests in C++, Javascript, and Python to demonstrate correctness
• Diagnose test failures, identify bugs in existing code, fix them, and prevent bugs from being introduced in new code
• Investigate the performance impact of code changes that may cause software performance regressions
• Interview candidates for advanced software engineering positions
• Develop and maintain expertise on cutting edge database, networking, and observability developments from industry and academia
• Lead development and project management of some of the largest projects across the company
• Collaborate with stakeholders and engineering teams across the company to jointly work on large initiatives
• Advise Product Management on technical product direction, engineering complexity and inter-project dependencies
• Collaborate with Product Management and Engineering leadership to define product roadmaps

• In the first month, you will have understood the high level architecture of MongoDB networking and observability, and fixed a few bugs
• In three months, you will have contributed to the development in C++ of a project slated for the next major release of MongoDB, and diagnosed and fixed a few customer or testing-reported issues
• In six months, you will have taken on code review responsibilities and are involved in reviewing the design for new features
• In twelve months, you will be leading the development of new features and initiatives, helping to mentor engineers on the team, and using your experience to drive the long-term technical roadmap of the Networking & Observability Team