Founding AI​/ML Research Engineer

A1 is a self-funded, independent AI group, focused on building a new consumer AI application with global impact. We’re assembling a small, elite team of ML, engineering and product builders who want to work on meaningful, high-impact problems.

About The Role

You will shape the core technical direction of A1 - model selection, training strategy, infrastructure, and long-term architecture. This is a founding technical role: your decisions will define our model stack, our data strategy, and our product capabilities for years ahead.

You won’t just fine-tune models – you’ll design systems: training pipelines, evaluation frameworks, inference stacks, and scalable deployment architectures. You will have full autonomy to experiment with frontier models (LLaMA, Mistral, Qwen, Claude-compatible architectures) and build new approaches where existing ones fall short.

What You’ll Be Doing

• Design new model architectures or adapt open-source frontier models
• Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation)
• Build data systems for high-quality synthetic and real-world training data
• Develop alignment, safety, and guardrail strategies
• Design evaluation frameworks across performance, robustness, safety, and bias
• Own deployment: GPU optimization, latency reduction, scaling policies
• Shape early product direction, experiment with new use cases, and build AI-powered experiences from zero
• Explore frontier techniques: retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, multimodal models

What You’ll Need

• Strong background in deep learning and transformer architectures
• Hands‑on experience training or fine-tuning large models (LLMs or vision models)
• Proficiency with PyTorch, JAX, or Tensor Flow
• Experience with distributed training frameworks (Deep Speed, FSDP, Megatron, ZeRO, Ray)
• Strong software engineering skills – writing robust, production‑grade systems
• Experience with GPU optimization: memory efficiency, quantization, mixed precision
• Comfortable owning ambiguous, zero‑to‑one technical problems end‑to‑end

Nice to Have

• Experience with LLM inference frameworks (vLLM, Tensor
  
  RT‑LLM, Faster Transformer)
• Contributions to open‑source ML libraries
• Background in scientific computing, compilers, or GPU kernels
• Experience with RLHF pipelines (PPO, DPO, ORPO)
• Experience training or deploying multimodal or diffusion models
• Prior work in a research lab (Google Brain, Deep Mind, FAIR, Anthropic, OpenAI)

Our Team & Culture

We operate as a dense, senior, high‑performance team. We value clarity, speed, craftsmanship, and relentless ownership. We behave like founders – we build, ship, iterate, and hold ourselves to a high technical bar.

If you value excellence, enjoy building real systems, and want to be part of a small team creating something globally impactful, you’ll thrive here.

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