About the Job
Company Description
As an Enterprise AI startup, our mission is to leverage cutting-edge artificial intelligence and machine learning technologies to tackle complex challenges faced by modern businesses. Our innovative solutions empower organizations to streamline operations, make data-driven decisions, and create groundbreaking customer experiences. Located in the heart of the San Francisco Bay Area, we foster a collaborative and dynamic work culture. Join us to shape the future of AI and solve impactful, real-world problems.
Role Description
This is a full-time, on-site role for a Senior / Founding Engineer (AI/ML) based in the San Francisco Bay Area.
Key responsibilities include designing, implementing, and optimizing machine learning models and algorithms to solve business problems, building scalable back-end systems and data pipelines to support AI/ML workflows, and collaborating with cross-functional teams to integrate AI-driven solutions into products.
A critical part of this role is working on search engine infrastructure at billion-record scale, including indexing, retrieval systems, and search results ranking. The role also involves debugging, performance optimization, and staying informed about the latest advancements in AI/ML and large-scale data systems.
Role Overview
We are a stealth, early-stage enterprise AI startup building foundational technology in the AI and data systems space. This is a founding engineering role for someone who wants to work hard technical problems early—when decisions matter and ownership is real.
You’ll work closely with the founder on core systems, helping define how the product is built and evolves. This role is suited for an experienced engineer who enjoys navigating ambiguity, making trade-offs, and building durable systems rather than polishing narrow features.
This is a full-time, on-site role.
What You’ll Work On
Designing and building scalable back-end systems, data pipelines, and search infrastructure that support AI and machine learning workflows
Developing and deploying machine learning models into production environments
Building and optimizing search systems at scale (billion+ records), including indexing, retrieval, and ranking pipelines
Working on large-scale data processing and system performance problems
Making early architectural decisions and iterating as requirements become clearer
Collaborating closely with a very small team in a high-ownership setting
This role emphasizes responsibility, judgment, and learning over task execution.
Technical Expectations
Strong foundation in computer science, including data structures, algorithms, and systems design
Proven experience building and operating large-scale back-end systems, data pipelines, and search infrastructure in production
Hands-on experience with search systems (indexing, query processing, ranking) at significant scale (ideally billion-record datasets)
Experience designing and deploying ML models beyond experimentation or research
Strong debugging skills and ability to optimize complex systems for performance and reliability
Familiarity with frameworks such as TensorFlow or PyTorch is helpful, but real production experience with data-intensive systems is essential
Ideal Background Signals
Experience working on data-intensive or AI-driven systems with large-scale search or retrieval components
Hands-on engineering ownership across system design, deployment, and iteration
Experience with search ranking, relevance tuning, or information retrieval systems
Comfort working in early-stage or ambiguous environments
Compensation and Benefits
Base salary range: $180,000 – $250,000
Equity: Meaningful equity as an early, founding engineer
Benefits: Standard benefits, including healthcare
Additional Job Application Terms
This job is part of LinkedIn’s Full-Service Hiring beta program. Eligibility is limited to candidates located in and performing services in the United States, excluding those based in Alaska, Hawaii, Nevada, South Carolina, or West Virginia.
We’re committed to making our hiring process as smooth and timely as possible, and we understand that waiting to hear back can add to the anticipation. If you’re a potential fit, our team will reach out within two weeks to progress you to the next stage. If you don’t hear from us in that time, we encourage you to explore other opportunities with our team in the future, and we wish you the very best in your job search.