ApplySarthi

Member of Technical Staff, Machine Learning

Profound

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1,087 open learning roles across 232 companies are on ApplySarthi right now, most of them in Bengaluru (61), Hyderabad (24), Delhi NCR (14).

What learning roles keep asking for: Machine learning (49%), Python (37%), LLMs (23%), PyTorch (23%), Deep learning (17%), AWS (14%), Generative AI (14%) — counted across their open postings here.

Member of Technical Staff jobs in the United States · Member of Technical Staff jobs in New York · Remote Member of Technical Staff jobs · Figma jobs · LLMs jobs · Machine learning jobs · MongoDB jobs

Profound has 72 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Profound.

Questions you are likely to be asked

  1. Why do you want to join Profound?
  2. What is your experience with LLMs? Tell me one thing you learned the hard way.
  3. What would you check first if a model's accuracy dropped after going live?
  4. When would you not use machine learning for a problem?
  5. Walk me through a model you built, from the data to how it was used.

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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. #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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Listed on ashby · posted 2025-09-04. ApplySarthi collects openings and links to application pages; the role is advertised by Profound, not by us.