AI Fund

About the Company

Who is AI Fund?

We are a team of AI pioneers, proven entrepreneurs, seasoned operators, and venture capitalists that collaborates with leading entrepreneurs to solve big challenges using artificial intelligence.

Founded in 2017 by Dr. Andrew Ng, AI Fund is backed with $176 million in capital by some of the leading VC firms and investors, including NEA, Sequoia, and Greylock.

How Are We Different?

We work with entrepreneurs during their startup's most critical and risky phase, from 0 to 1. At the earliest stages, your company strategy is still being formed, and you're still on the path to demonstrating your idea's full potential - this is a reality we understand. This is the period when decisions on product strategy, market fit, and team are most critical, moving fast and fixing parts of your business when you have limited resources is a challenge.

We believe the best way to help entrepreneurs is by providing our time, expertise, and resources to help flesh out these key strategic decisions. Making the right decisions at the right time can often make the difference. We are here to improve these dynamics, at a time when the help matters the most.

Why Work With AI Fund?

Getting a startup from idea to Series A funding is not easy. We've been there and understand the challenges you must overcome. Whether you desire limited help and just want access to our unique ecosystems of AI experts and entrepreneurs or you would like our full support, we are interested in the opportunity to help in your success.

We are flexible in how we work with companies, but ultimately, we are here to maximize your chance of success and accelerate getting your company to market. We provide the capital, expertise, and resources to accelerate the work required to minimize risks in your startup, help you rise above the noise, and make your company more attractive to new investors.

Listed Jobs

Company Name

AI Fund

Job Title

Software Engineer - Infrastructure

Job Description

**Job Title:** Software Engineer – Infrastructure **Role Summary:** Design, develop, and maintain core infrastructure components of a machine‑learning inference platform. Enable reliable, high‑performance model deployment, scaling, and monitoring using Python, Go, and Kubernetes. Collaborate with cross‑functional teams to automate workflows and optimize resource utilization. **Expactations:** - 1‑3 years of professional software or infrastructure engineering experience. - Ability to work independently and in a team, communicate technical concepts clearly. - Proactive learning of ML/AI infrastructure practices and continuous improvement of system reliability and performance. **Key Responsibilities:** - Develop infrastructure services for model serving in Python and Go. - Implement and manage Kubernetes deployments and orchestration layers. - Build and enhance monitoring and logging for model performance metrics. - Design resource‑management solutions for distributed ML workloads. - Automate deployment pipelines and infrastructure provisioning. - Participate in technical discussions, code reviews, and architecture planning. **Required Skills:** - Proficiency in Python; Go proficiency a plus. - Hands‑on experience with Kubernetes, containers, and related tooling. - Understanding of distributed systems and basic monitoring/logging tools (e.g., Prometheus, Grafana). - Fundamental knowledge of machine‑learning model serving concepts. - Strong problem‑solving, collaboration, and written/oral communication skills. **Required Education & Certifications:** - Bachelor’s degree or higher in Computer Science, Engineering, or a related field. - No specific certifications required; relevant coursework or projects in cloud infrastructure or ML preferred.

San francisco, United states

On site

Fresher

21-09-2025

Company Name

AI Fund

Job Title

Software Engineer - Model Performance

Job Description

**Software Engineer - Model Performance** **Role Summary:** Develop and optimize machine learning model inference performance, focusing on large language models (LLMs), in a fast-paced startup environment. **Expectations:** - Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or related field. - 3+ years of software engineering experience in backend systems or ML optimization. **Key Responsibilities:** - Implement and productionize optimization techniques (quantization, speculative decoding, chunked prefill) for ML inference. - Debug and improve performance in ML frameworks (PyTorch, TensorRT, TensorRT-LLM) and GPU codebases (CUDA). - Scale optimization strategies across diverse ML models, with emphasis on LLMs. - Collaborate to design and deliver end-to-end performance-focused solutions. - Own projects from conceptualization to deployment. **Required Skills:** - Proficiency in Python or C++. - Strong familiarity with ML libraries (PyTorch, TensorRT, TensorRT-LLM). - Applied experience in LLM optimization techniques (e.g., quantization, continuous batching). - Deep understanding of GPU architecture and CUDA. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent technical discipline. - Demonstrated experience with open-source ML frameworks and model performance tuning.

San francisco, United states

On site

12-10-2025