Home › Companies › NationGraph › (PHD) Applied Machine Learning Engineer
(PHD) Applied Machine Learning Engineer
NationGraph · San Francisco · On Site · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | NationGraph |
| Title | (PHD) Applied Machine Learning Engineer |
| Normalized title | - |
| Department / team | Engineering / Engineering |
| Location | San Francisco, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-23 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from NationGraph. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Engineering. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | NationGraph |
| Source | cb1dc962-a3dc-48ca-803d-10463cb9ff32 |
| ATS provider | Ashby |
Description
About NationGraph
NationGraph is making public sector data accessible and actionable for businesses selling to cities, counties, state agencies, schools, and special districts. NationGraph’s data and intelligence engine provides buying signals derived from millions of public sector sources. Founded in 2024, NationGraph is dedicated to making uncommon knowledge common, because public data should actually be public. Learn more at nationgraph.com
You’ll Join A Team That:
Has successfully built, scaled, and sold companies in the past.
Built software infrastructure processing billions of dollars in transactions.
Is backed by world-class VCs and operating partners who’ve invested in, and built, iconic companies.
About The Role:
Build and productionize end-to-end ML pipelines.
Mine data from the web through large-scale crawling and scraping to power our models and insights.
Transform unstructured text data into structured knowledge with NLP, entity recognition, and custom models.
Build and improve text classification models to organize complex data.
Optimize retrieval-augmented generation (RAG) systems used in our product.
Drive our data strategy by identifying new data sources.
Solve open-ended technical problems, teaching, learning, and iterating with the team.
Work primarily in Python and SQL.
What You’ll Need:
A quantitative background (e.g., computer science, physics, math, or engineering)
A strong mathematical and statistical foundation
A doctorate degree in a quantitative field
Proficiency in Python
A strong sense of ownership and ability to work on open-ended technical problems to drive commercial impact
A passion for learning and growth, and for uncovering insights in complex data
Excellent problem-solving, communication, and collaboration skills in a fast-paced environment
What You'll Get From Us:
Founder-Level Exposure. Work closely with the CEO/CTO on all aspects of the business.
A zero bureaucracy environment. We believe in moving extremely fast and making bold decisions without red tape.
Solve real-world problems that matter and work directly with interesting founders in their journey as they improve the infrastructure our government relies on at every level.
Working with great people with a diversity of thought, an eagerness to learn, a boldness to challenge the status quo, and a deep care for the work we put out. If you align with us here, we strive to shape the working environment as such.
Benefits:
Competitive salary + early-stage equity 💰
Unlimited PTO ✈️
High-quality health insurance, dental & vision coverage 🏥
Company provided lunches (Mon - Thur) 🍜
We believe in-person work is our default.
We’re building a team of people who desires to work side-by-side and shape the culture of a growing company. In our experiences, some of the best ideas come from being in the room, feeling the pain, hearing the nuance, and catching the details that are easy to miss.
At the same time, we’re flexible and supportive when working-from-home is needed to maintain a healthy, balanced work environment.
Full job record
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| Source ID | cb1dc962-a3dc-48ca-803d-10463cb9ff32 |
| Board ID | cb1dc962-a3dc-48ca-803d-10463cb9ff32 |
| Provider | ashby |
| Provider Job Key | d0e175ca-155f-48e0-93fe-ae06ab7f7705 |
| Title | (PHD) Applied Machine Learning Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Engineering |
| Team | Engineering |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/NationGraph/d0e175ca-155f-48e0-93fe-ae06ab7f7705 |
| Apply URL | https://jobs.ashbyhq.com/NationGraph/d0e175ca-155f-48e0-93fe-ae06ab7f7705/application |
| First Seen At | 2026-05-29 06:53:21Z |
| Last Seen At | 2026-06-23 09:50:19Z |
| Last Checked At | 2026-06-23 09:50:19Z |
| Last Changed At | 2026-05-29 06:53:21Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=NationGraph/date=2026-06-23/2026-06-23T09-50-13-516Z-470441cdb630a8d2e1ea28339e6653f41a916a72e79dafcb3a84973eaabfa477.json |
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