Senior Applied Scientist - Knowledge Graphs & AI

Outreach is hiring a Senior Applied Scientist - Knowledge Graphs & AI for a remote role open to applicants in India. Level rates it ; you can apply on Outreach.

Level's read on this job

Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
This is listed as a remote role.
The posting mentions Databricks, Python and PyTorch among its tools and skills.
Level classes it as a senior role.
Outreach has 22 other open roles on Level.

AI in this role

Build knowledge graph extraction pipelines and machine learning models for enterprise sales reasoning systems.

databrickspythonpytorchneo4jllms

nlpmachine-learningknowledge-graphsapplied-science

About Outreach Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few.

About the job:

We are looking for an Associate Applied Scientist to join a dynamic and innovative AI platform team. If you are passionate about applying machine learning to knowledge graphs and reasoning systems at scale, this is an opportunity to build core components of Outreach's per-tenant knowledge graph while developing deep expertise under the guidance of senior scientists.
Our team is building a per-tenant contextual knowledge graph that captures the full complexity of each customer's sales environment: accounts, deals, contacts, rep behaviors, competitive landscape, and the signals buried in calls, emails, and CRM activity. This graph powers contextual reasoning across the platform, driving next-best-action recommendations, deal risk signals, coaching suggestions, and competitive intelligence. In this pivotal role, you will design the underlying representations, extraction pipelines, and reasoning layers that make this possible, working closely with cross-functional engineering and product teams to deliver innovative, scalable, and reliable AI capabilities with direct impact on revenue outcomes.
This role is ideal for someone with strong ML fundamentals who wants to build deep expertise in knowledge graphs and applied NLP in a fast-moving product environment.

How we rate this

Senior Applied Scientist - Knowledge Graphs & AI at Outreach rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist - Knowledge Graphs & AI is an open job at Outreach.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Hyderabad and is marked remote.
The job was posted on July 3, 2026.
Seniority: senior.
Applications are handled by Outreach. Apply on Outreach

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningKnowledge GraphsApplied ScienceDatabricksPythonPyTorchNeo4j

Also common in applied scientist jobs at this level

Python C++Java Deep learning LLM Generative AI

Pay

Typical applied scientist job: $172k

This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where knowledge graphs was part of your work. What did you do?
Tell me about a project where applied science was part of your work. What did you do?
Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

List these exact terms on your resume: NLP, Machine learning, Knowledge Graphs, Applied Science, and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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