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Member of Technical Staff, Machine Learning

New York, New York · 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
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Work setting
On-site stated — work setting 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.
Location type: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data — team source

Before you apply

Sponsorship
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Apply at Profound

What you’ll work on

Full posting
  • Build and deploy NLP models at scale for classification, ranking, and clustering

  • Design LLM workflows for topic discovery, briefs, drafts, and publish-ready content

  • Build prompt and template libraries with retrieval for cited, grounded generation

  • Create evaluation frameworks for factuality, tone, safety, and originality

  • Instrument content performance and run experiments to improve quality, cost, and latency

From the employer’s posting
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
Instrument content performance across AEO and SEO visibility, engagement, and conversion, and run experiments to improve quality, cost, and latency

What you’ll bring

All qualifications

Core 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.

Posting record

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Open 4 monthsWe first saw this listing 142 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
Jun 2, 2026 · 142 days ago
Recorded sightings
173
Last seen by us
Oct 21, 2026
Employer says posted
Sep 4, 2025

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Job description

View original posting ↗

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.

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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.
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