CAREERS
Build the infrastructure that makes AI work.
We are a rapidly growing AI infrastructure technology company based in the Washington, DC area. Our goal is to transform the economics of generative AI by harnessing compute resources more intelligently – delivering exceptional training and inference performance at scale with significantly lower cost.
We believe we’re building something ambitious that will have a positive impact on the world. Our team is collaborative, technical, and customer-focused. We work remotely, but get together regularly for in-person meetings and strategy sessions.
Have a look at the positions below and reach out if you’re interested.
Open positions
AI Systems / Platform Engineer
Responsibilities
To architect, develop, bring-up, deploy and maintain large multi core CPU/GPU platforms with and without CUDA framework, for running AI workloads at scale. This position requires deep understanding of systems programming, customization in the builds of OS & Drivers, enabling virtualization at platform, systems and applications layers of technology stack. We are looking for candidates with a positive attitude and inclination towards fast paced & iterative process of development, deployment and testing.
Qualification Requirements
Must be a U.S. citizen
Strong foundation in Computer Science and Operating Systems
Excellent problem-solving and analytical skills
Ability to work in a hybrid environment
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Prior experience in Embedded Systems is necessary, and AI & Machine Learning experience is a plus
An overall 5+ years of related experience
Technical Stack Requirements
Proficiency in Object Oriented Programming with C/C++, Python, using Databases and Networking libraries & packages to develop secure & scalable system applications.
Experience in any RTOS/Embedded Software Development - Device driver, BSP programming & Driver development and OS Customization for custom H/W platforms.
Experience in GPU, CUDA Programming. Any experience with AI workload customization at platform level will be a plus.
Experience in building Board Support Packages (BSP), Troubleshooting system failures at board/platform level issues.
Experience in working with virtualization technologies for VMs, Hypervisor and Containers & their Orchestration (Docker, Kubernetes or similar) is desirable
Nice To Have
Familiarity of working with public clouds - GCP, AWS Services (Cloudfunctions, GKE, Lambda, ECS etc)
Knowledge of developing and deployment for Distributed Computing Infrastructure will be beneficial.
A background in data science or data analysis
Experience of working with technical leadership in a fast-growing start up environment
AI Application / ML Engineer
Responsibilities
To architect, develop, deploy, maintain AI Applications and Inferencing & Training workloads (LLM’s) for scale. These applications involve building & supporting AI Agents, Agentic AI workflows, RAGs and other related sub systems in AI Application eco systems. We are looking for candidates with a positive attitude and inclination towards fast paced & iterative process of development, deployment & testing.
Qualification Requirements
Must be a U.S. citizen
Strong foundation in Computer Science and Operating Systems
Excellent problem-solving and analytical skills
Ability to work in a hybrid environment
Bachelor’s or Master’s degree in Computer Science, Data Science or Engineering, or related field
Prior experience in AI and Machine Learning is necessary
An overall 5+ years of related experience
Technical Stack Requirements
Proficiency in Object Oriented Programming with C/C++, Python, JavaScript using Databases and Networking libraries to develop secure & scalable system applications.
Experience as Web Application Full Stack Developer with focus on AI/ML applications - Development, Maintenance and Deployments at Scale.
Experience in development in AI/ML eco systems of NLP and other LLMs models (open-source or commercial APIs like GPT etc)
Experience in the use of AI/ML frameworks & tools such as PyTorch or TensorFlow.
Experience of working with secure retrieval-based architectures, data pipelines and embedding databases.
Experience of working with Containers & their Orchestration (Docker, Kubernetes or similar).
Nice To Have
Familiarity with virtualization technologies for VMs, Hypervisor is a plus
Familiarity of working with public clouds - GCP, AWS Services (Cloudfunctions, GKE, Lambda, ECS etc) is necessary
Knowledge of developing, troubleshooting applications at scale for distributed computing will be beneficial
Experience of working with technical leadership in a fast-growing start up environment
