A1 · 13 hours ago
Principal Machine Learning Engineer
Palo Alto, CA
Full-time
Hybrid
Lead/StaffA1 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 including training pipelines, inference systems, evaluation tooling, and deployment.
Computer Software
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, in partnership with research leadership
Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies
Collaborate closely with application engineering to integrate ML systems cleanly 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
Qualification
Required
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), and ability to learn others quickly
Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray)
Strong software engineering fundamentals – you write 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
Preferred
Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer
Contributions to open-source ML or systems libraries
Background in scientific computing, compilers, or GPU kernels
Experience with RLHF pipelines (PPO, DPO, ORPO)
Experience training or deploying multimodal or diffusion models
Experience with large-scale data processing (Apache Arrow, Spark, Ray)
Company
A1
A1 is research and product group focused on building essential, next-gen applications that benefits the wider society, not the exclusive few.
Founded in 2025Malaysia, MY
11-50 employeesFunding
Current Stage
Early StageCompany data provided by crunchbase