Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Applied Data Scientist
Reads like an ML Engineer role: training models and running them in production.
San Francisco, CA
Open 6 months, first seen by us 205 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
On-site — work setting source
We are now building our Silicon Valley engineering team — a small, senior group focused on next-generation AI research and product. Location: San Francisco, SoMa — minimum 4 days per week in-office. What you'll do
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full- Time
From the employer’s posting
Before you apply
- Work authorization
- Must already have the right to work in the US
Must be authorized to work in the US without current or future employer sponsorship
What you’ll work on
Full postingBuild and maintain ML models for classification, extraction, and trend detection
Design experiments and benchmarks to measure accuracy and reduce bias
Apply NLP techniques like embeddings, NER, and text classification to data pipelines
Move models into production with a partner engineering team, owning monitoring and drift detection
Build evaluation frameworks for AI-generated outputs across product use cases
From the employer’s posting
Build and maintain ML models for classification, extraction, trend detection, and predictive scoring
Design experiments and benchmarks to measure model accuracy, reduce bias, and validate outputs at scale
Apply NLP techniques — embeddings, NER, text classification — to real-world data pipelines
Partner with engineering to move models from experimentation to production; own monitoring and drift detection
Build evaluation frameworks for AI-generated outputs across multiple product use cases
Posting record
Report an errorOpen 6 monthsWe first saw this posting 205 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 23, 2026205 days ago
- Recorded sightings
- 118
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 205
Up longer than most. Similar jobs usually come down between day 8 and day 76.
From 5,460 similar postings that came down. Coming down is not always a hire.
Hophr is hiring
4 open jobs
- No new data jobs since May
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
• 3–5 years of applied data science; minimum 2 years working with NLP or large-scale text data in production. • Strong Python (pandas, scikit-learn, PyTorch or TensorFlow); proficient in SQL. • Demonstrated track record of shipping models into production, not just producing analysis.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Draup is a Series A-funded agentic AI company building the intelligence layer for how global enterprises make workforce and go-to-market decisions. We work with 250+ enterprise clients — including 5 of the Fortune 10 — processing 1B+ job descriptions, 850M+ professional profiles, and signals from 100+ labor databases.
We are now building our Silicon Valley engineering team — a small, senior group focused on next-generation AI research and product.
Location: San Francisco, SoMa — minimum 4 days per week in-office.
What you'll do
• Build and maintain ML models for classification, extraction, trend detection, and predictive scoring on large structured and unstructured datasets.
• Design experiments and benchmarks to measure model accuracy, reduce bias, and validate outputs at scale.
• Apply NLP techniques — embeddings, NER, text classification — to real-world data pipelines.
• Partner with engineering to move models from experimentation to production; own monitoring and drift detection.
• Build evaluation frameworks for AI-generated outputs across multiple product use cases.
What we require
• BS/MS in Statistics, Computer Science, Applied Mathematics, or a quantitative field.
• 3–5 years of applied data science; minimum 2 years working with NLP or large-scale text data in production.
• Strong Python (pandas, scikit-learn, PyTorch or TensorFlow); proficient in SQL.
• Demonstrated track record of shipping models into production, not just producing analysis.
• Experience with embedding models and semantic similarity at enterprise scale.
• No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship.
Employment type
Full- Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
• Experience with embedding models and semantic similarity at enterprise scale. • No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship. Employment type