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Founding Machine Learning Engineer

Bjak
City of London
6 days ago
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Transform language models into real-world, high-impact product experiences.

A1 is a self-funded AI group, operating in full stealth. We’re building a new global consumer AI application focused on an important but underexplored use case.


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.


Why This Role Matters
  • You are creating the intelligence layer of A1’s first product, defining how it understands, reasons, and interacts with users.

  • Your decisions shape our entire technical foundation — model architectures, training pipelines, inference systems, and long-term scalability.

  • You will push beyond typical chatbot use cases, working on a problem space that requires original thinking, experimentation, and contrarian insight.

  • You influence not just how the product works, but what it becomes, helping steer the direction of our earliest use cases.

  • You are joining as a founding builder, setting engineering standards, contributing to culture, and helping create one of the most meaningful AI applications of this wave.


What You’ll Do
  • Build end-to-end training pipelines: data → training → eval → inference


  • Design new model architectures or adapt open-source frontier models


  • Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation)


  • Architect scalable inference systems using vLLM / TensorRT-LLM / DeepSpeed


  • 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 It’s Like to Work Here
  • You take ownership - you solve problems end-to-end rather than wait for perfect instructions


  • You learn through action - prototype → test → iterate → ship


  • You’re calm in ambiguity - zero-to-one building energises you


  • You bias toward speed with discipline - V1 now > perfect later


  • You see failures and feedback as essential to growth


  • You work with humility, curiosity, and a founder’s mindset


  • You lift the bar for yourself and your teammates every day


Requirements
  • 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 TensorFlow


  • Experience with distributed training frameworks (DeepSpeed, 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, TensorRT-LLM, FasterTransformer)


  • 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


  • Experience in large-scale data processing (Apache Arrow, Spark, Ray)


  • Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI)


What You’ll Get
  • Extreme ownership and autonomy from day one - you define and build key model systems.


  • Founding-level influence over technical direction, model architecture, and product strategy.


  • Remote-first flexibility


  • High-impact scope—your work becomes core infrastructure of a global consumer AI product.


  • Competitive compensation and performance-based bonuses


  • Backing of a profitable US$2B group, with the speed of a startup


  • Insurance coverage, flexible time off, and global travel insurance


  • Opportunity to shape a new global AI product from zero


  • A small, senior, high-performance team where you collaborate directly with founders and influence every major decision.


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.


About A1

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


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