Member of Technical Staff, Machine Learning
New York, United States
- Pay
$180,000–260,000/year · BaseAnnual period assumed — pay source
This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expected base salary range is $180,000 to $260,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring. #LI-DNI
Read the full posting- Work setup
On-site stated — work setup source
Location This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expected base salary range is $180,000 to $260,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingBuild and deploy NLP models at scale for classification, ranking, clustering, topic extraction, and summarization
Design LLM workflows for context and content generation end to end, including topic discovery, brief creation, outlines and drafts, revision loops, and publish-ready assets
Partner with engineering to instrument events, maintain data pipelines, and uphold high data quality and observability
From the employer’s posting
What you’ll do Build and deploy NLP models at scale for classification, ranking, clustering, topic extraction, and summarization Design LLM workflows for context and content generation end to end, including topic discovery, brief creation, outlines and drafts, revision loops, and publish-ready assets
Build and deploy NLP models at scale for classification, ranking, clustering, topic extraction, and summarization Design LLM workflows for context and content generation end to end, including topic discovery, brief creation, outlines and drafts, revision loops, and publish-ready assets Develop prompt and template libraries aligned to brand voice and channel, including blogs, landing pages, help docs, and ads, with retrieval for evidence-grounded generation and citations
Transform large text datasets into production features and signals that drive product insights Partner with engineering to instrument events, maintain data pipelines, and uphold high data quality and observability Collaborate with product, data, and go-to-market teams on success metrics and experiments that move customer-facing KPIs
What you’ll bring
All qualificationsCore experience
- Proven experience shipping machine learning systems in production at scale, especially with large text data
- Ability to innovate when off-the-shelf solutions do not fit the problem
- Ownership mindset and comfort operating in a fast-paced environment
- Hands-on experience building LLM content systems including prompting, templating, retrieval or RAG, guardrails, and evaluations
- Experience working in cross-functional, high-performance teams
Qualification wording
Proven experience shipping machine learning systems in production at scale, especially with large text data
Ability to innovate when off-the-shelf solutions do not fit the problem
Ownership mindset and comfort operating in a fast-paced environment
Hands-on experience building LLM content systems including prompting, templating, retrieval or RAG, guardrails, and evaluations
Experience working in cross-functional, high-performance teams
Tools in this posting
- Python
- SQL
- MongoDB
Source — Tool mentions in context
- Hands-on experience building LLM content systems including prompting, templating, retrieval or RAG, guardrails, and evaluations - Fluency in SQL and strong Python skills with modern machine learning tooling - Strong grasp of machine learning and generation quality metrics, with the ability to design offline and online evaluations and monitoring
Profound is the marketing platform for the age of AI search. The way brands reach people is being rewritten — AI models like ChatGPT, Perplexity, and Google AI Mode are now the answer layer between companies and their customers. We built the platform marketers use to understand, measure, and win in that world: the analytics, intelligence, and agent automation that turn AI search from a threat into a competitive advantage. We went from 0 to a $1B valuation in 18 months. Revenue grew 100x last year. Our customers include 15% of the Fortune 500 like Walmart, Wayfair and U.S. Bank, and innovators like Ramp, MongoDB, and Figma. We are backed by Sequoia, Kleiner Perkins, LSVP, and Khosla Ventures — and we are moving fast enough that the people joining now are building the playbook everyone who comes after them will run. As an AI and ML Engineer, you will design, build, and ship large scale NLP and LLM systems that power classification, ranking, clustering, topic discovery, and content generation. You will own workflows from data to deployment, partner across product and engineering, and turn real user conversations into production features and publish-ready content that drives visibility, engagement, and conversion.
Job description
Profound is the marketing platform for the age of AI search. The way brands reach people is being rewritten — AI models like ChatGPT, Perplexity, and Google AI Mode are now the answer layer between companies and their customers. We built the platform marketers use to understand, measure, and win in that world: the analytics, intelligence, and agent automation that turn AI search from a threat into a competitive advantage.
We went from 0 to a $1B valuation in 18 months. Revenue grew 100x last year. Our customers include 15% of the Fortune 500 like Walmart, Wayfair and U.S. Bank, and innovators like Ramp, MongoDB, and Figma. We are backed by Sequoia, Kleiner Perkins, LSVP, and Khosla Ventures — and we are moving fast enough that the people joining now are building the playbook everyone who comes after them will run.
As an AI and ML Engineer, you will design, build, and ship large scale NLP and LLM systems that power classification, ranking, clustering, topic discovery, and content generation. You will own workflows from data to deployment, partner across product and engineering, and turn real user conversations into production features and publish-ready content that drives visibility, engagement, and conversion.
What you’ll do
Build and deploy NLP models at scale for classification, ranking, clustering, topic extraction, and summarization
Design LLM workflows for context and content generation end to end, including topic discovery, brief creation, outlines and drafts, revision loops, and publish-ready assets
Develop prompt and template libraries aligned to brand voice and channel, including blogs, landing pages, help docs, and ads, with retrieval for evidence-grounded generation and citations
Create evaluation frameworks for generated content, including factuality, coverage, tone, safety, and originality, with rubric-based LLM evaluations, human-in-the-loop review, and red teaming
Instrument content performance across AEO and SEO visibility, engagement, and conversion, and run experiments to improve quality, cost, and latency
Transform large text datasets into production features and signals that drive product insights
Partner with engineering to instrument events, maintain data pipelines, and uphold high data quality and observability
Collaborate with product, data, and go-to-market teams on success metrics and experiments that move customer-facing KPIs
Who you are
Proven experience shipping machine learning systems in production at scale, especially with large text data
Hands-on experience building LLM content systems including prompting, templating, retrieval or RAG, guardrails, and evaluations
Fluency in SQL and strong Python skills with modern machine learning tooling
Strong grasp of machine learning and generation quality metrics, with the ability to design offline and online evaluations and monitoring
Ability to innovate when off-the-shelf solutions do not fit the problem
Experience working in cross-functional, high-performance teams
Clear communication with both technical and non-technical partners
Ownership mindset and comfort operating in a fast-paced environment
Excited by ownership of the entire product analytics function at an early stage company
Motivated by shaping how usage is measured and how product decisions are made
Interested in close collaboration with product, engineering, and go-to-market teams
Comfortable in a fast-paced environment with trust, autonomy, and responsibility
Drawn to competitive compensation and meaningful equity
Location
This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact.
For this role, the expected base salary range is $180,000 to $260,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.
#LI-DNI
Note: All official communication from Profound will come from a @tryprofound.com email address. If you're contacted by anyone using a different domain, please disregard and report it as spam.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expected base salary range is $180,000 to $260,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring. #LI-DNI
- Location & working pattern
New York, United States
Location This is an on-site role based in our NYC or SF office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expected base salary range is $180,000 to $260,000. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 156
- Last seen by us
- Oct 10, 2026
- Employer says posted
- Sep 4, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.