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.

About the Role

As a Member of Technical Staff on our Data Platform team, you will be instrumental in creating innovative data tools that transform raw inputs into high-quality datasets for ML training and labeling. Your work will focus on designing and building robust pipelines for data transformation, filtering, analysis, and cleaning. We are looking for data engineers who deeply understand ML and are passionate about developing next-generation tools that empower our data curation processes at scale.

This is a good role for you if you:

• Have extensive experience working in ML environments, with a keen understanding of how high-quality data drives model performance.
• Are skilled at designing and implementing data tools that streamline the process of dataset creation, data annotation, and labeling.
• Possess a strong background in building systems for efficient data transformation, filtering, analysis, and cleaning.
• Thrive in innovative, fast-paced settings where you can directly impact the quality and reliability of training data for cutting-edge AI applications.

Responsibilities include:

• Designing, building, and maintaining state-of-the-art data tools that convert raw data into high-quality datasets for ML training and labeling.
• Developing robust workflows and pipelines for data transformation, filtering, analysis, and cleaning that enhance dataset quality.
• Collaborating with ML researchers, data scientists, and engineers to ensure our data tools meet the rigorous standards required for enterprise-grade AI.
• Continuously evaluating and integrating emerging technologies to keep our data curation processes at the forefront of innovation.
• Driving the evolution of our data platform to support scalable, efficient, and effective data annotation and labeling pipelines.

Employee Pay Disclosures

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

Interview Process

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:

1. Hiring Manager Conversation – An initial discussion with the hiring manager to assess fit and alignment.
2. Technical Interview – A deep dive with an Inflection Engineer to evaluate your technical expertise.
3. 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.