We’re partnering with a well-funded, seed-stage startup to help build their early engineering team. They’re hiring two more AI/ML Engineers and are open to candidates at the Senior, Staff, or Principal level.
If you're excited about building a product from the ground up, we’d love to hear from you. Check out the job description below to learn more.
As the AI/ML Engineer, you’ll be one of the early technical hires and play a key role in building the 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.)
