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Salary: USD 200,349.5 - 260,912.6 / annual
6sense is hiring a Senior Machine Learning Engineer to join its AI team, reporting to the Head of AI. The company's mission is to multiply growth, retention, and efficiency by turning signals into actionable intelligence for go-to-market teams.
In this role, you will own machine learning problems end-to-end—from data exploration and modeling through production deployment, monitoring, and iteration. You'll build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows. Your work will power products like RevvyAI, a conversational GTM intelligence platform, and reach customers through APIs and MCP servers.
Key responsibilities include developing ranking, recommendation, prediction, and optimization models that prioritize explainability over black-box approaches. You'll partner closely with Product and Go-to-Market teams to translate ambiguous business problems into shipped capabilities. You'll also improve the performance, scalability, and reliability of production ML systems, help shape AI platform architecture, and mentor other engineers.
Required qualifications: 8+ years building and deploying production ML systems with clear end-to-end ownership. Strong foundation in machine learning and applied statistics, with hands-on expertise in NLP, transformers, embeddings, and retrieval-based systems. Practical experience with modern GenAI tools (LangGraph, LangChain, Amazon Bedrock). Strong Python skills and experience with distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent). Solid grasp of feature engineering, model evaluation, and MLOps. A product mindset focused on customer impact. Excellent communication skills to explain complex work to technical and non-technical audiences.
Nice-to-have: RAG architectures, vector databases, prompt engineering, PyTorch/TensorFlow, B2B SaaS or enterprise AI product experience.
The team is distributed across the US and India. This is a build-and-ship role where AI is the product, not a feature.
