AI Software Engineer, Nexus

• If you love optimizing ML workloads and making complex systems run smoothly in production, this one's for you
• 3+ years of experience in software engineering, preferably with exposure to ML systems in production
• Strong skills in Python, Go, or Java, and a solid understanding of system performance fundamentals
• Experience with containerization (Docker, Kubernetes) and deploying services in the cloud (AWS, GCP, or Azure)
• Solid understanding of model serving architectures and techniques for optimizing latency and throughput
• Comfort with performance tuning and profiling of ML model execution
• A practical mindset and eagerness to own production systems from build to run

Desirable

• We’re looking for an AI Software Engineer focused on Inference to help us bring powerful AI models to life — fast, efficient, and at scale
• This role is all about building the systems that deliver real-time predictions, keeping latency low and performance high
• At our startup, speed matters — not just in how our models perform, but in how quickly we learn, ship, and grow
• You’ll be a core part of the engineering team, collaborating closely with researchers and product engineers to build scalable inference systems that support everything we do
• Design and optimize lightning-fast inference pipelines for both real-time and batch predictions
• Deploy and scale machine learning models in production across cloud and containerized environments
• Leverage frameworks like TensorFlow Serving, TorchServe, or Triton to serve models at scale
• Monitor performance in the wild — build tools to track model behavior, latency, and reliability
• Work with researchers to productionize models, implement model compression, and make inference as efficient as possible
• Solve problems fast — whether it’s a scaling bottleneck, a failed deployment, or a rogue latency spike
• Build internal tools that streamline how we deploy and monitor inference workloads