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LeadFull-timePyTorchAIML
Salary Range
$153,000 - $207,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time. You will be responsible for turning research direction into working, production-grade ML systems, owning the execution layer of A1’s intelligence.
Key Responsibilities
- →Build and own end-to-end ML pipelines spanning data, training, evaluation, inference, and deployment
- →Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation
- →Architect and operate scalable inference systems, balancing latency, cost, and reliability
- →Design and maintain data systems for high-quality synthetic and real-world training data
- →Implement evaluation pipelines covering performance, robustness, safety, and bias
- →Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies
- →Collaborate closely with application engineering to integrate ML systems into backend, mobile, and desktop products
- →Make pragmatic trade-offs and ship improvements quickly, learning from real usage
- →Work under real production constraints: latency, cost, reliability, and safety
Requirements
- ✓Strong background in deep learning and transformer-based architectures
- ✓Hands-on experience training, fine-tuning, or deploying large-scale ML models in production
- ✓Proficiency with at least one modern ML framework (e.g. PyTorch, JAX)
- ✓Experience with distributed training and inference frameworks
- ✓Strong software engineering fundamentals – writing robust, maintainable, production-grade systems
- ✓Experience with GPU optimization, including memory efficiency, quantization, and mixed precision
- ✓Comfort owning ambiguous, zero-to-one ML systems end-to-end
- ✓A bias toward shipping, learning fast, and improving systems through iteration
