Data Scientist (LLM)
Data Scientist (LLM)
Posted on :
25-08-2025
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1 Vacancy
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Job Description
Who we are:
Who Were Looking For:
Were hiring a Data Scientist focused on Large Language Models to join our AI R&D team. Youll work on designing training and optimizing LLMs that power real product features and internal tools. Youll touch everything from architecture and data preparation to multi-scale training and evaluation.
This is not a prompt engineering or RAG-focused role. Were looking for someone who gets the math understands the models and knows how to write code that scales.
Youll work side-by-side with engineers MLOps and product teams to make our LLMs smarter faster and more useful.
What Youll Do:
- Train and fine-tune LLMs using multi-GPU and distributed setups.
- Analyze model performance debug failures and implement improvements.
- Work with curated and synthetic datasets including classification and generation tasks.
- Design experiments track results and iterate quickly with tools like MLflow.
- Write clean production-ready code and collaborate via GitHub.
- Push boundaries: think about architecture memory efficiency scale and cost.
What Were Looking For:
- LLM understanding: You know how these models work under the hood - transformer internals tokenization embeddings etc.
- Stats and ML fundamentals: You have a solid foundation in statistics machine learning and optimization.
- Coding skills: You write Python well. Youve worked with PyTorch or JAX. You dont fear Bash or git.
- Training experience: Youve trained models beyond notebooks. Bonus if youve worked with mixed precision DeepSpeed or multi-node training.
- Systems mindset: You understand trade-offs - throughput vs memory latency vs accuracy.
- Good judgment: You know when to read a paper when to read a stack trace and when to rewrite the dataloader or part of the LLM architecture.
Bonus Points:
- Experience with Hugging Face Transformers Datasets Accelerate.
- Familiarity with Kubernetes Ray or custom training infra.
- Exposure to embeddings classification tasks or token-level losses.
- Ability to mentor or guide junior researchers or engineers.
How We Hire:
- Online assessment: Online assessment: technical logic and fundamentals (Math/Calculus Statistics Probability Machine Learning/Deep Learning Code).
- Technical interview: dive into theory and reasoning (no code).
- Cultural interview.
If you are not willing to take an online quiz do not apply.
Diversity and inclusion:
We believe in social inclusion respect and appreciation of all people. We promote a welcoming work environment where each CloudWalker can be authentic regardless of gender ethnicity race religion sexuality mobility disability or education.
Employment Type
Full-Time
Key Skills
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