We’re partnering with a well-funded, seed-stage startup to help build their early engineering team. They’re hiring two AI Engineers and are open to candidates at the Senior, Staff, or Principal level.

If you're excited about building from the ground up and think you’re a great fit, we’d love to hear from you. Check out the job description below to learn more.

As our Founding Staff AI/ML Engineer, you’ll be one of the first technical hires and play a key role in building our core machine learning systems from the ground up. You’ll own the entire lifecycle; from prototyping models to deploying production-grade systems while working closely with the founding team to influence product direction and technical architecture.

This is a rare opportunity to have deep impact, massive ownership, and the chance to shape the culture, systems, and trajectory of a category-defining company.

What You’ll Do

• Design, build, and deploy scalable ML systems that power our core product.
• Own end-to-end development: problem formulation, data pipelines, model training, evaluation, and production deployment.
• Collaborate with product and engineering to translate business goals into ML solutions.
• Evaluate and apply state-of-the-art techniques in LLMs, deep learning, classical ML, and generative AI.
• Establish best practices for model reproducibility, monitoring, and performance tracking.
• Build and scale our MLOps infrastructure (training pipelines, experiment tracking, deployment tooling).
• Recruit and mentor future ML/AI hires and help grow the team and culture.

Qualifications:

• 8+ years of experience in Artificial Intelligence, Machine Learning and Software Engineering.
• Strong foundation in ML/DL algorithms, statistical modeling, and data processing.
• Deep experience with modern ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
• Hands-on experience with LLMs, transformers, or other foundation models.
• Proven experience building and deploying production-grade ML systems.
• Strong software engineering skills (Python, APIs, cloud infra, containerization).
• Familiarity with ML pipelines and platforms (e.g., Airflow, MLflow, SageMaker, Vertex AI).
• Startup mindset: ownership, bias for action, comfort with ambiguity, and a builder mentality.
• Degree in Computer Science, Machine Learning, Mathematics, or related field. (PhD or MS preferred but not required with equivalent experience.)