Salary for research scientist

Average salary

3300 £

Basic salary	700 £
Maximum Wage	7500 £

700 £
Lowest

4100 £
Average

7500 £
Highest

research scientist - How much money do you make working at this position?

The average salary for the research scientist position is 3300 £

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RISE TECHNICAL RECRUITMENT 329 reviews Based on 2 job offers	5000 £
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Salary in companies

ANTHROPIC	20625 £	700 £ 20625 £
AUTODESK	12241 £	700 £ 20625 £
ADLIB	7500 £	700 £ 20625 £
MICROTECH GLOBAL	6666 £	700 £ 20625 £
MCGREGOR BOYALL CONSULTING	5625 £	700 £ 20625 £
HARNHAM	5600 £	700 £ 20625 £
CRANLEIGH SCIENTIFIC	5416 £	700 £ 20625 £
PARK STREET	5120 £	700 £ 20625 £
RISE TECHNICAL RECRUITMENT	5000 £	700 £ 20625 £
TALENT WORKS INTERNATIONAL	5000 £	700 £ 20625 £

Comment on the job position of research scientist

Requirements

advanced degree in Computer Science, Machine Learning, or a related field
strong software engineering skills with a proven track record of building complex systems
expertise in Python and experience with deep learning frameworks
familiarity with large-scale machine learning, particularly in the context of language models
ability to balance research goals with practical engineering constraints
strong problem-solving skills and a results-oriented mindset
work on high-performance, large-scale ML systems
familiarity with GPUs, Kubernetes, and OS internals
excellent communication skills and ability to work in a collaborative environment
experience with language modeling using transformer architectures
care about the societal impacts of your work
knowledge of reinforcement learning techniques
background in large-scale ETL processes
ph.D. or equivalent experience in microbiology, molecular biology, or a related field
proven expertise in Campylobacter research, with a strong publication record demonstrating contributions to the field
an understanding of CRISPR would be beneficial but not essential
knowledge of phage-bacteria interaction would be a plus
excellent analytical and problem-solving skills, with the ability to work both independently and collaboratively in a fast-paced research environment
proven experience in working on grants and managing projects, demonstrating effective time and effort management to meet deadlines
strong written and oral communication skills, with the ability to effectively communicate scientific concepts, writing papers and reports

Responsibility

conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
independently lead small research projects while collaborating with team members on larger initiatives
design, run, and analyze scientific experiments to advance our understanding of large language models
optimize and scale our training infrastructure to improve efficiency and reliability
develop and improve dev tooling to enhance team productivity
contribute to the entire stack, from low-level optimizations to high-level model design
lead the development and scaling of machine learning models at the intersection of research and product
collaborate with the engineering teams to find and resolve distributed deep learning training bottlenecks such as checkpointing, model/optimizer compression etc
collaborate with the engineering teams to find and resolve distributed deep learning training bottlenecks such as checkpointing, model/optimizer compression etc…
optimize data flows through the model and overall architecture
leverage frameworks such as Open Neural Network Exchange and TensorRT to create high performance model endpoints
writing robust, testable code that is well documented and easy to understand
analyze errors and provide solutions to problems that arise
present the results of your work to collaborators and leadership
leverage distributed deep learning frameworks, such as DeepSpeed, FSDP etc…, to perform scaling experiments with the support of engineering and data teams
conduct research to develop solutions against Campylobacter pathogenesis in poultry
optimize Guided Biotics to enhance efficiency in targets train Campylobacter
collaborate with cross-functional colleagues to integrate CRISPR technology into our product candidate
improve the delivery efficiency of the Guided Biotic into the target strain Campylobacter
analyse experimental data, interpret results, and present findings to internal stakeholders and external partners through written reports and oral presentations

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