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We're seeking a Software Engineer to join our development team supporting our software group.

What makes this role unique is your direct impact on AI-powered innovation - you'll be building intelligent systems that drive the development of next-generation cloud technologies.
You'll work at the fascinating intersection of AI driven automation and cloud platform development, implementing automation solutions that directly enhance the productivity of our engineers. Unlike typical roles, you'll have the opportunity to influence both AI implementation and core architecture while collaborating with cloud technology experts.
The position offers rare exposure to cutting-edge cloud computing technology combined with the latest advances in artificial intelligence. You'll be part of a team that values technical excellence, working in an environment where your ideas can quickly transform from concept to reality.
In this role you will create groundbreaking platforms that directly shape the way we work. You'll develop smart automation solutions, implement AI-driven tools and workflows and be part of AI transformation.

Be part of an elite team developing cutting-edge AI infrastructure automation solutions supporting Annapurna Labs' innovative technology development. Shape the future of cloud computing while working with state-of-the-art cloud and AI technologies in a fast-paced environment.

Key job responsibilities
* Develop and deploy AI-powered solutions and AWS cloud services that transform development workflows.
* Lead technical innovation by driving architectural decisions and GenAI technology adoption.
* Champion AI transformation across engineering teams through education and hands-on implementation.
* Partner with elite cloud teams to identify opportunities and deliver cutting-edge solutions.
* Ensure system excellence through participation in on-call rotations and reliability initiatives.

As an ML Software Engineer with a focus on low-level and CUDA-based optimizations, you will play a key role in shaping the design, performance, and scalability of machine learning inference systems. Youll work on deeply technical challenges at the intersection of GPU acceleration, systems architecture, and ML deployment.
Your expertise in CUDA, C/C++, and performance tuning will be crucial in enhancing runtime efficiency across heterogeneous computing environments. Youll collaborate with designers, researchers, and backend engineers to build production-grade ML pipelines that are optimized for latency, throughput, and memory use, contributing directly to the infrastructure powering next-generation AI products.This role is ideal for an engineer with strong systems-level thinking, deep familiarity with GPU internals, and a passion for pushing the boundaries of performance and efficiency in machine learning infrastructure.

Responsibilities
Design and implement highly optimized GPU-accelerated ML inference systems using CUDA and low-level parallelism techniques
Optimize memory, compute, and data flow to meet real-time or high-throughput constraints
Improve the performance, reliability, and observability of our inference backend across diverse compute targets (CPU/GPU)
Collaborate with cross-functional teams (including researchers, developers, and designers) to deliver efficient and scalable inference solutions
Contribute to ComfyUI and internal infrastructure to improve the usability and performance of model execution flows
Investigate performance bottlenecks at all levels of the stack-from Python to kernel-level execution
Navigate and enhance a large, complex, production-grade codebase
Drive innovation in low-level system design to support future ML workloads

Were looking for a hands-on, independent DevOps Engineer to lead the companys cloud infrastructure and operations. This is a standalone position for someone with at least two years of practical experience managing cloud environments end-to-end. Youll take full ownership of AWS infrastructure, ensuring system security, performance, and reliability. Youll work closely with developers and product managers, bridging development and operations, while driving automation and scalable solutions.





Responsibilities
Manage and optimize the companys AWS infrastructure.
Configure and monitor product firewalls and security tools.
Lead product deployments and updates.
Perform Java profiling (CPU & memory), analyze bottlenecks, and optimize system performance.
Build and maintain an advanced monitoring system for the companys products, covering performance, availability, and key metrics.
Write scripts to automate infrastructure and operational tasks.
Collaborate with developers and product teams on CI/CD and infrastructure.

Come join the Agentic AI science team in building the next generation models for intelligent automation.

We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.