Machine Learning Engineer (LLM) at Bjak
Deutschland, , Germany -
Full Time


Start Date

Immediate

Expiry Date

27 Nov, 25

Salary

0.0

Posted On

27 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Relevance, Deep Learning, Toxicity, Distillation, Data Structures

Industry

Information Technology/IT

Description

TRANSFORM LANGUAGE MODELS INTO REAL-WORLD APPLICATIONS

We’re building AI systems for a global audience. We are living in an era of AI transition - this new project team will be focusing on building applications to enable more real world impact and highest usage for the world.
This role is a global role with hybrid work arrangement - combining flexible remote work with in-office collaboration at our HQ. You’ll work closely with regional teams across product, engineering, operations, infrastructure and data to build and scale impactful AI solutions.

REQUIREMENTS

  • Strong experience in transformers, deep learning, and fine-tuning methods (LoRA/QLoRA, SFT, distillation).
  • Proficiency with PyTorch (preferred) or TensorFlow.
  • Skilled in prompt engineering and dataset curation for alignment with tone, safety, and trust.
  • Familiar with evaluation metrics: perplexity, toxicity, relevance.
  • Strong software engineering foundations in algorithms, data structures, and clean code practices.
Responsibilities

WHY THIS ROLE MATTERS

You’ll fine-tune state-of-the-art models, design evaluation frameworks, and bring AI features into production. Your work ensures our models are not only intelligent, but also safe, trustworthy, and impactful at scale.

WHAT YOU’LL DO

  • Fine-tune & adapt - Use LoRA/QLoRA to optimize open-source models (LLaMA, Mistral, Gemma)
  • Engineer prompts & curates data - Craft prompts and datasets that reflect tone, brand voice, and safety.
  • Evaluate models – Build metrics pipelines for perplexity, toxicity, and relevance to ensure safe and high-quality outputs.
  • Deploy & monitor – Scale models into production with performance optimization and monitoring for drift.
  • Collaborate & deliver – Partner with product, engineering, and design teams to launch user-facing AI features.
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