About the role
<div class="content-intro"><p><strong>Our Mission:</strong></p> <p>6sense's mission is to multiply what matters: growth, retention, and efficiency.&nbsp; We envision a future where companies, teams and people reach their full potential.</p> <p><strong>Our People:</strong></p> <p>People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging. &nbsp;Every 6sensor plays a part in defining the future of our industry-leading technology.&nbsp; 6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.&nbsp; We want 6sense to be the best chapter of your career.&nbsp;</p></div><p><strong>
About
the Role :</strong></p> <p>We’re hiring a Sr. ML Engineer to join our AI team. Signals tell you what happened. Our job is to explain why — and that is the problem you will work on. You will build the intelligence that turns a trillion daily signals into cited, explainable answers about why an account matters, why now, and who is deciding. Your models power products customers use every day, including RevvyAI, our conversational GTM intelligence product, and reach their stack through our APIs and MCP server.&nbsp;</p> <p>This is a build-and-ship role, not a research role. You will own problems end to end, work directly with&nbsp;Product and Go-to-Market, and see your work reach customers. You’ll join a team distributed across the&nbsp;US and India, at a company where AI is the product rather than a feature</p> <p><strong>What will you own: :</strong></p> <ul> <li>Own machine learning problems end to end — from data exploration and modeling through deployment,&nbsp;monitoring, and iteration in production.</li> <li>Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.</li> <li>Develop ranking, recommendation, prediction, and optimization models that are explainable rather than&nbsp;black-box.</li> <li>Partner with Product and Go-to-Market to turn ambiguous business problems into shipped capabilities.</li> <li>Improve the performance, scalability, and reliability of production ML systems, and help shape AI platform&nbsp;architecture.</li> <li>Explain your work clearly to technical and non-technical audiences, and engage with customers when&nbsp;needed.</li> <li>Mentor engineers and raise the bar for engineering excellence</li> </ul> <p><strong>What We’re Looking For :</strong></p> <ul> <li>6+ years of industry experience building and deploying machine learning systems in production, with clear end-to-end ownership.</li> <li>Strong foundation in machine learning and applied statistics, with hands-on depth in NLP, transformers, embeddings, and retrieval-based systems.</li> <li>Practical experience with modern GenAI tooling such as LangGraph, LangChain, or Amazon Bedrock.</li> <li>Strong Python skills and experience building distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent).</li> <li>Solid grasp of feature engineering, model evaluation, and MLOps practices.</li> <li>A product mindset — you want to build AI products customers use, and you measure yourself on customer impact.</li> <li>Excellent communication: you can explain complex technical work clearly, tell the story of what you’ve built and why, and hold your own with product and business partners.</li> <li>Comfort with ambiguity and the judgment to drive execution independently.</li> </ul> <p><strong>
