- Company Name
- Cubiq Recruitment
- Job Title
- Applied Scientist
- Job Description
-
Job Title: Applied Scientist
Role Summary:
Early‑career researcher focused on advancing context‑aware agentic systems for enterprise use. Drive research from concept to production, leveraging ML models (LLMs, multimodal, structured reasoning, etc.) to build, evaluate, and deploy agent capabilities that integrate with business workflows.
Expectations:
- Finalize or recently completed a PhD from a top university in Physics, Mathematics, Machine Learning, Computer Science, or a closely related field.
- Demonstrated publication record at leading conferences (NeurIPS, ICML, ICLR, ACL, CVPR, ICCV, EMNLP).
- Ability to translate high‑level research into production‑ready code and prototypes.
- Strong collaborative skills with engineering teams in a fast‑moving product environment.
- Self‑motivated, curious, and eager to address complex technical challenges with real business impact.
Key Responsibilities:
1. Develop and iterate core models for context‑aware enterprise agents covering planning, retrieval, grounding, and multi‑step decision pipelines.
2. Conduct cutting‑edge research on ML frontiers relevant to agentic systems (LLMs, multimodal models, structured reasoning, data generation, video‑text modeling, etc.).
3. Design and implement robust training, evaluation, and benchmarking pipelines for new model variants and agent behaviors.
4. Prototype agent capabilities and collaborate closely with engineering to transform prototypes into production‑quality features.
5. Analyse agent failure modes in real customer environments and devise methods to improve reliability, grounding, and actionability.
6. Contribute to internal research papers, technical memos, and publish externally where appropriate.
Required Skills:
- Expertise in modern ML architectures (transformers, diffusion, retrieval‑augmented systems, reinforcement learning, etc.).
- Strong coding proficiency in Python; experience with at least one major ML framework (PyTorch, JAX, TensorFlow).
- Capability to bridge theoretical research with practical implementation in a production setting.
- Excellent analytical and problem‑solving abilities.
- Effective written and verbal communication skills for technical documentation and presentation.
Required Education & Certifications:
- PhD (or equivalent) in Physics, Mathematics, Machine Learning, Computer Science, or a related field from a top‑tier university. No additional certifications required.