We are looking for a Machine Learning Engineer to help build and develop our ML capabilities at RADAR. The role requires extensive collaboration with teams and functions across the company ranging from product and customer success to engineering, data science and research.
As a Forward Deployed Engineer, you’ll sit at the intersection of engineering, product, and customer success, extending Vanta’s product to solve real problems and ensure successful adoption. You’ll support unique customer requirements across integrations, data transformations, and reporting outcomes, combining software and systems engineering fundamentals with empathy for customer challenges.
Raise the technical bar for the team by setting architectural direction. Design, build and scale robust, high-throughput, low latency recommender systems that power product features used by tens of millions of users every day. Collaborate cross-functionally to shape ML-driven product roadmaps, balancing speed of iteration with long-term system complexity and scalability.
Design, build, and scale customer-facing AI agents that transform how finance teams work. You’ll own projects from design to production and set the standard for applied AI at Moss. Architect agents that provide a transparent audit trail of all reasoning steps and enable user intervention at any time. Seamlessly integrate customer data into agent workflows while maintaining trust, security, and adaptability. Shape Moss’s AI engineering practices, mentor peers, and influence product strategy.
Lead the design and architecture of backend services that power real-time model inference and bidding decisions for our OpenRTB platform. Collaborate with data scientists and machine learning engineers to deploy, monitor, and optimize ML models that influence real-time bidding strategies, pricing decisions, and targeting. Optimize performance and cost-efficiency across the backend infrastructure.
As a Full Stack Engineer at Cyngn, you will play a crucial role in developing our innovative fleet management system for autonomous industrial vehicles. Your diverse skill set will allow you to seamlessly move between backend and frontend tasks, helping to create a cohesive and efficient system that empowers our customers to optimize their automated workflows and maximize operational efficiency.
As the Staff Software Engineer for the SaaS platform team, you will be crucial in developing Cyngn's cutting-edge fleet management system for autonomous industrial vehicles and collaborate with product and engineering teams to design, implement, deploy, and maintain a robust cloud-based solution that enables real-time control and monitoring of autonomous vehicles in the field.
Design and deploy backend systems powering production-grade applications in a cloud-native, containerized environment. Deploy robust APIs, orchestrate services with Kubernetes, and contribute to event-driven systems architecture. Build and deploy backend services using Docker and Kubernetes, you’ll deploy resilient, scalable deployments on GCP.
As a transpiler engineer, you will help build the foundations of a system that turns source code into human language. The Driver Transpiler blends traditional compiler elements with LLM content generation to generate exhaustive, structured documentation of software. This architecture fuses traditional compiler-like static analysis and data structures with highly structured use of large language models (LLMs).
Joining the “Digital Workflow” team, you will design and implement web-based applications to automate industrial machines - from simulating them in the Cloud, all the way to operating them on the shopfloor - including backend and databases, user interfaces, CI/CD pipeline, and everything in-between. You will get the chance to work with our robot systems (including robotic arms and three-axis machines) and the tablet that shop-floor operators use to control and interact with their equipment.