Senior Research Scientist (Architectures Research)
New
J
JobgetherArtificial Intelligence
SpainFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Required Skills
- PythonMachine LearningDeep Learning
Requirements
- PhD in machine learning or a closely related field, or equivalent depth of research experience.
- Deep understanding of transformers, attention mechanisms, language-model training and modern neural network architectures.
- Strong track record of research publications or comparable evidence of original and impactful research.
- Proven ability to formulate research hypotheses, design rigorous experiments and extract meaningful conclusions from complex or ambiguous results.
- Strong implementation skills in Python and experience with a modern deep-learning framework.
- Hands-on experience training, evaluating or experimenting with machine-learning models at scale.
- Strong technical communication skills and the ability to independently lead research projects.
- Experience with long-context modeling, memory systems, sparse or linear attention, model distillation, distributed training or efficient inference is particularly valuable.
- Ability to collaborate effectively with engineering and research teams while maintaining ownership of individual research initiatives.
- Curiosity, intellectual rigor and a strong interest in solving challenging problems at the frontier of AI.
Responsibilities
- Formulate original and high-impact research questions around model architectures, efficiency, reasoning, memory and adaptation.
- Translate research ideas into rigorous experimental programs with clear hypotheses, evaluation criteria and measurable outcomes.
- Design, implement and evaluate architectural changes at meaningful model scales.
- Research efficient, sparse and adaptive attention mechanisms, long-context architectures, persistent memory and selective computation.
- Investigate new approaches to reasoning, continual adaptation and dynamic inference.
- Develop methods that preserve or improve model quality while reducing training and inference costs.
- Conduct large-scale model training and evaluation, interpreting ambiguous experimental results and drawing robust conclusions.
- Collaborate with engineering teams to turn research concepts into efficient, scalable implementations.
- Publish original research and contribute to open-source models, methodologies and research tools.
- Mentor researchers and contribute to defining priorities, methodologies and the long-term direction of the research stream.
View Full Description & ApplyYou'll be redirected to the employer's site
