Member of Technical Staff, Machine Learning
At a glance
Senior Machine Learning Engineering role at Profound. New York · full-time · $160,000–$250,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and deploy large-scale text models for classification, ranking, clustering, topic extraction and summarization
- Create end-to-end LLM workflows for discovering topics, drafting content, revising it and producing publishable assets
- Develop brand- and channel-specific prompt templates, with retrieval that grounds generated content in evidence and citations
- Set up content-quality checks for factuality, coverage, tone, safety and originality, combining automated reviews with human input
- Track content visibility, engagement and conversion, then run tests to improve quality, cost and latency
What you bring
- A track record of putting machine learning systems into production at scale, particularly systems built around large text datasets
- Practical experience building LLM content systems with prompting, templates, retrieval or RAG, safeguards and evaluation
- Strong Python ability, SQL fluency and working knowledge of modern machine learning tools
- Knowledge of generation-quality metrics and how to evaluate and monitor systems both offline and in production
Who this fits
This role suits a senior builder who wants ownership from data through deployment and enjoys working across product, engineering and data teams. It is an on-site position in New York City or San Francisco.
From the employer
Profound is the fastest-growing AI marketing platform, used by 15% of the Fortune 500 including Comcast, Estée Lauder, and Walmart, and innovators like Ramp, MongoDB, and Figma. It is where marketing teams do the work: research, briefs, content, campaigns, reporting, all in one place, alongside agents that carry the load with them.
Built on 2B+ real user prompts and growing, Profound’s data shows you what people ask AI and what the models say back. Profound's AI Marketer joins that data with deep context about our customers to find the opportunities worth acting on, and then puts agents to work: automating reporting, drafting content, auditing pages for readability, running competitive research. It measures what works and gets better every day.
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.
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.