Senior Software Engineer, Machine Learning

<p>Software Engineer, Machine Learning (MLOps &amp; Data)</p> <p>&nbsp;</p> <p><strong>A Career with Point72’s Surveillance </strong><strong>Team</strong></p> <p>On the Knowledge Graph Intelligence team, you’ll work alongside product managers, engineers, and data scientists to build the next generation of intelligent systems through graph technology. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision-making and enhance how we build and operate our platforms and applications.</p> <p><strong>What you’ll do</strong></p> <p>In this data-heavy role, you will design and build mission-critical infrastructure that powers our machine learning lifecycle, from large-scale data processing and feature engineering to model training, real-time deployment, and monitoring. Specifically, you will:</p> <ul> <li>Architect and implement the full lifecycle of ML models, from data ingestion to production inference, contributing to the design of our next-generation, event-driven architecture, using technologies like gRPC, Kafka, and high-performance API frameworks, like FastAPI, Spring WebFlux, and Axum.</li> <li>Engineer and automate robust, large-scale data processing pipelines (ETL/ELT) using tools like Spark, dbt, and workflow orchestrators, and lead the design and implementation of our Feature Store strategy.</li> <li>Own the MLOps framework for model training, versioning, and deployment, including CI/CD pipelines, automated workflows, and experiment tracking and evaluation tooling.</li> <li>Implement sophisticated deployment strategies, including canary, blue-green, shadow, and A/B testing, to ensure safe, zero-downtime releases, and optimize inference performance for LLMs and other large models.</li> <li>Leverage cutting-edge tools and techniques like quantization and compilation to maximize throughput and minimize latency.</li> <li>Collaborate with data scientists to develop models and optimize model performance for low-latency serving using techniques like Python performance tuning.</li> <li>Define, provision, and manage our cloud infrastructure using Terraform, working hands-on with a wide array of cloud services across compute, storage, and machine learning platforms.</li> </ul> <p><strong>&nbsp;</strong></p> <p><strong>What’s REQUIRED</strong></p> <ul> <li>5+ years of experience in a software, data, or ML engineering role.</li> <li>Strong proficiency in SQL.</li> <li>