A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time.
You will work on core ML systems under the guidance of senior engineers. This role is for builders who want to grow their judgment by shipping real ML systems in production.
Build and improve ML components across data, training, evaluation, and inference.
Fine-tune and adapt models as part of larger production systems.
Implement evaluation and testing to understand model behavior.
Help build and maintain data pipelines for real-world and synthetic data.
Debug model issues, performance problems, and production incidents.
Ship improvements iteratively and learn from real user feedback.
Work closely with senior ML engineers and product teams.
Work under real production constraints: latency, cost, reliability, and safety
Python
PyTorch / JAX
Production ML systems running on GPUs
Strong foundations in machine learning and modern neural architectures.
Some hands-on experience training, fine-tuning, or deploying ML models.
Comfortable writing production-quality code and learning new tools quickly.
Curious, coachable, and eager to learn from real systems in production.
Able to work through ambiguity with guidance and grow ownership over time.
Bias toward shipping, iteration, and continuous improvement.
Our organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company’s mission.
If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.
Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.
We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.
bjakcareer