Founding AI/ML Research Engineer at Bjak

Stockholm, Stockholm County, Sweden -

Full Time

Start Date

Immediate

Expiry Date

20 Mar, 26

Salary

0.0

Posted On

21 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Transformer Architectures, Large Models, PyTorch, JAX, TensorFlow, Distributed Training, GPU Optimization, Model Architectures, Training Pipelines, Evaluation Frameworks, Inference Systems, Data Systems, Alignment Strategies, Safety Strategies, Deployment

Industry

Software Development

Description

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.

Responsibilities

You will build end-to-end training pipelines and design new model architectures or adapt existing ones. Additionally, you will shape the early product direction and experiment with new use cases.