BJAK

Founding AI/ML Research Engineer

BJAK

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇧🇪 Belgium

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Job Level

Mid-LevelSenior

Tech Stack

ApachePyTorchRaySparkTensorflow

About the role

  • 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

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
  • Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) (Nice to Have)
  • Contributions to open-source ML libraries (Nice to Have)
  • Background in scientific computing, compilers, or GPU kernels (Nice to Have)
  • Experience with RLHF pipelines (PPO, DPO, ORPO) (Nice to Have)
  • Experience training or deploying multimodal or diffusion models (Nice to Have)
  • Experience in large-scale data processing (Apache Arrow, Spark, Ray) (Nice to Have)
  • Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI) (Nice to Have)
Benefits
  • 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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
deep learningtransformer architecturestraining large modelsfine-tuning modelsGPU optimizationdistributed training frameworksevaluation frameworksalignment strategiessafety strategiesguardrail strategies
Soft skills
problem-solvingownershipadaptabilitycreativitycollaboration