This is a rare opportunity to join a Series A AI data and services company as a Founding ML Engineer, working directly alongside the founding team to build and scale core machine learning systems from the ground up. You will bridge research and engineering — designing, training, and shipping production-grade models for top AI frontier labs — while helping shape the company's technical culture and infrastructure.
The company specializes in high-quality training and post-training data, reinforcement learning environments, and intelligent agents that accelerate AI model performance for both frontier labs and enterprises. This is a high-ownership, high-impact role: your work will directly establish the foundation for how the team delivers measurable ML outcomes.
Visa sponsorship is not available for this role.
Задачи
Build and optimize end-to-end ML pipelines, from data ingestion through to deployment
Implement and fine-tune LLMs, embeddings, and generative models for real-world applications
Develop efficient training and inference systems leveraging distributed compute
Partner with data and product teams to translate ideas into measurable ML impact
Contribute to model monitoring, evaluation, and continual learning frameworks
Establish best practices in model versioning, reproducibility, and scalability
Требования
3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer
Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX
Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization
Hands-on experience with distributed systems, cloud ML infrastructure (AWS, GCP, or Azure), and MLOps tooling such as Weights & Biases or MLflow
Comfort working with large datasets and high-throughput systems
Strong bias for action, ability to work autonomously, and genuine eagerness to build something from scratch
Условия
Salary range: $220,000 – $300,000 USD annually
Early-stage equity commensurate with a founding team role
Opportunity to define technical culture and ML infrastructure at the ground level
LOCATION
On-site in Mountain View, California, United States
Remote work is not available for this position
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ashbyОсновная публикация · 2026-08-15
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