
Junior AI Scientist
Workster · Location not stated
Weak hiring record · median 460 days open
All reasons
- Open 445 days
- 84% of this employer's openings are over 60 days old
- No location stated
In its favour
- Still listed on the employer's own board
Workster is partnering with a cutting-edge AI startup on a mission to give models the ability to act autonomously—running code, fixing systems, and analysing data—so humans can focus on strategy and creativity. Their work goes beyond traditional language models, focusing on AI that can perform real, meaningful tasks. If you’re excited by the idea of applying advanced AI research to create practical, high-impact solutions, this is a great opportunity to join a small, fast-moving team where your contributions will be seen and valued.
#### **Your Role**
- Assist in research, prototyping, and feature development to advance their Agentic LAM from proof-of-concept to production.
- Work in selected areas of Machine Learning and AI, such as:
- **–** Running and fine-tuning Large Language Models (LLMs).
- **–** Implementing Retrieval-Augmented Generation (RAG) pipelines.
- **–** Preparing and cleaning datasets for training and evaluation.
- **–** Designing and running tests to improve accuracy, safety, and reliability.
- Write clear, maintainable Python code for experiments and prototypes.
- Collaborate closely with senior scientists to learn best practices in AI optimisation, scaling, and evaluation.
- Track experiments and analyse results using tools like Weights & Biases or MLflow.
#### Your Qualifications
- You don’t need to know everything on the list — but you should bring **depth in at least one or two areas** and the curiosity to learn more.
For example
- Strong fundamentals in linear algebra, probability, calculus, or optimisation.
Hands-on experience with
- **–** Python, Jupyter, Git.
- **–** PyTorch or TensorFlow.
- **–** Hugging Face Transformers for simple fine-tuning.
- **–** Vector databases (e.g., FAISS or Qdrant).
- Understanding of evaluation metrics such as accuracy, F1, or perplexity.
- Familiarity with Docker and basic cloud concepts is a plus.
- A proactive, learning-driven mindset.
- No formal degree required—skills, passion, and initiative matter
#### The Offer
- Hybrid work in Lisbon with the option for multi-week remote blocks.
- Competitive salary plus equity potential.
- Subsidised apartment if relocating.
- Health insurance, modern hardware, and a personal learning budget.
- Company-funded travel to global AI conferences and events.
- Work directly with experienced AI engineers and researchers, with strong mentorship opportunities.
- Fast-paced startup environment with real ownership from day one.
### Benefits
Skills
- Machine Learning
- LLM
- Retrieval-Augmented Generation
- Python
- Weights & Biases
- MLflow
- Git
- PyTorch
- TensorFlow
- Hugging Face Transformers
- Vector Databases
- FAISS
- Qdrant
- Docker
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