3 дня назад
Research Scientist (Applied LLMs)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Scientist (Applied LLMs) (AI-driven drug discovery): Building and applying large language models, machine learning algorithms, and scalable training and inference frameworks to solve complex biological and medical problems with an accent on model architecture, post-training, reasoning, tool use, and reinforcement learning. Focus on designing novel LLM techniques, analyzing experimental results, and leading interdisciplinary research into computational biology and chemistry challenges.
Location: London, United Kingdom; hybrid work with office attendance required 3 days per week
Company
develops AI models and predictive and generative systems for drug discovery and digital biology.
What you will do
- Advance machine learning research focused on applying large language models to drug discovery.
- Develop and refine LLM-driven approaches for complex biological and medical use cases.
- Create novel ML techniques and prepare data for model training and application.
- Analyze and tune experiments to guide future research directions.
- Implement and scale training and inference engineering frameworks.
- Present findings and collaborate with ML scientists, biologists, chemists, and other domain experts.
Requirements
- PhD or equivalent practical experience in a technical field.
- Deep experience building and applying LLMs to novel problem spaces, including model architectures, training, deployment, post-training, reasoning, test-time scaling, tool use, alignment, agents, reinforcement learning, and fine-tuning.
- Strong knowledge of linear algebra, calculus, statistics, the current LLM landscape, and real-world datasets.
- Experience with JAX, PyTorch, or TensorFlow and scientific tools such as NumPy, SciPy, or Pandas.
- Depending on experience, project supervision, technical leadership, or people management may be expected.
- Ability to work in a hybrid model and attend the London office 3 days per week.
Nice to have
- PhD in machine learning or computer science, postdoctoral experience, publications, or contributions to ML codebases.
- Background in biology, medicine, computational chemistry, bioinformatics, or related scientific fields.
- Experience with biological or chemical datasets and scientific software.
- Experience in multi-parameter optimization, large-scale deep learning, generative models, graph neural networks, drug discovery, computer vision, 3D graphics, robotics, or applied reinforcement learning.
Culture & Benefits
- Interdisciplinary collaboration across machine learning, biology, chemistry, and other scientific fields.
- Culture centered on curiosity, creativity, rigor, initiative, integrity, determination, and collaboration.
- Shared learning and an environment designed to support employees and diverse perspectives.
- Equal employment opportunities and accommodations for additional needs.
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