Senior Machine Learning Engineer
Seeking a highly skilled Senior Machine Learning Engineer to join our AI team and play a pivotal role in developing state-of-the-art discovery and extraction systems. As a senior member of the team, you will lead the design, development, and deployment of sophisticated machine learning models, specifically focusing on search ranking, recommendation engines, and high-precision document extraction. You will work on complex data science problems while collaborating closely with business, product, and engineering teams to deliver impactful AI-driven features that are central to our product offering.This is a unique opportunity to be at the forefront of innovation, leveraging advanced AI technologies like LLMs and vector databases to transform an industry ripe for digital disruption.Minimum QualificationsEducation: Bachelor’s or Master’s degree (PhD preferred) in Science or Engineering with strong programming and analytical skills.ML Expertise: Strong conceptual understanding of machine learning principles, specifically in NLP, Search, or Ranking.Technical Skills: Hands-on experience implementing ML projects in Python using libraries like NumPy, scikit-learn, and pandas.Deep Learning: Proficiency in training and fine-tuning deep learning models using PyTorch or TensorFlow.Leadership: Proven ability to lead technical initiatives from concept to operation while navigating complex challenges.Preferred QualificationsSpecialized Infrastructure: Deep experience with Vector Databases (e.g., Pinecone, Milvus) and optimizing embedding models for retrieval.Fine-tuning: Experience fine-tuning LLMs for specialized domain tasks and ranking signals.AI Agent Orchestration: Hands-on experience with agentic frameworks (e.g., LangGraph, AutoGen, or CrewAI) for building complex, multi-step reasoning chains.Planning & Memory: Experience implementing agentic "memory" (long-term/short-term) and planning strategies (like ReAct or Tree of Thoughts).Data Structures: Expert knowledge of algorithms and data structures.Research & Community: A track record of publications in top-tier conferences (e.g., NeurIPS, SIGIR, KDD, ACL) or significant contributions to open-source ML projects.