Inflection AI is a public benefit corporation leveraging our world class large language model to build the first AI platform focused on the needs of the enterprise.
Who we are:
Inflection AI was re-founded in March of 2024 and our leadership team has assembled a team of kind, innovative, and collaborative individuals focused on building enterprise AI solutions. We are an organization passionate about what we are building, enjoy working together and strive to hire people with diverse backgrounds and experience.
Our first product, Pi, provides an empathetic and conversational chatbot. Pi is a public instance of building from our 350B+ frontier model with our sophisticated fine-tuning (10M+ examples), inference, and orchestration platform. We are now focusing on building new systems that directly support the needs of enterprise customers using this same approach.
Want to work with us? Have questions? Learn more below.
As a Member of Technical Staff on our MLOps / ML Infrastructure team, you will be at the core of designing, building, and operating the systems that power our machine learning workflows—from model training to production deployment. Your work will be critical in developing control planes and robust tools around ML services, ensuring our platform is scalable, secure, and resilient. We’re looking for candidates with production operations experience, strong open-source backgrounds, and hands-on expertise in managing distributed clusters.
This is a good role for you if you:
- Have extensive experience operating ML systems in production environments and building tools to manage them.
- Are highly proficient in managing distributed clusters using Kubernetes (K8s), SLURM, and Ray.
- Possess a strong open-source background, with experience at top-tier companies, and are comfortable leveraging community-driven tools as well as proprietary solutions.
- Are security-aware and knowledgeable about best practices for safeguarding production systems, even though the role is not exclusively security-focused.
- Thrive in dynamic, innovative environments where pushing the boundaries of ML infrastructure is a daily pursuit.
Responsibilities include:
- Designing and implementing scalable ML infrastructure to support end-to-end machine learning workflows—from training and deployment to production operations.
- Building and managing control planes and tools that ensure efficient, secure, and reliable operation of our ML services.
- Collaborating closely with ML researchers, data scientists, and engineers to optimize system performance and resource utilization.
- Leveraging distributed computing frameworks (Kubernetes, SLURM, Ray) to orchestrate ML workloads across diverse environments.
- Continuously evaluating and integrating emerging technologies to enhance scalability, efficiency, and security across our ML systems.
- Maintaining a strong security posture through the adoption of best practices in infrastructure design and operations.
At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary will fall in the range of approximately $175,000 - $350,000 depending on experience. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range.
Benefits
Inflection AI values and supports our team’s mental and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include:
- Diverse medical, dental and vision options
- 401k matching program
- Unlimited paid time off
- Parental leave and flexibility for all parents and caregivers
- Support of country-specific visa needs for international employees living in the Bay Area
Apply: Please apply on Linkedin or our website for a specific role.
After speaking with one of our recruiters, you’ll enter our structured interview process, which includes the following stages:
- Hiring Manager Conversation – An initial discussion with the hiring manager to assess fit and alignment.
- Technical Interview – A deep dive with an Inflection Engineer to evaluate your technical expertise.
- Onsite Interview – A comprehensive assessment, including:
- A domain-specific interview
- A system design interview
- A final conversation with the hiring manager
Depending on the role, we may also ask you to complete a take-home exercise or deliver a presentation.
For non-technical roles, be prepared for a role-specific interview, such as a portfolio review.
Decision Timeline
We aim to provide feedback within one week of your final interview.