An MSc or PhD-level AI engineer or scientist is required. A fast-paced, high-growth biotechnology company requires the assistance of an LLM expert in artificial intelligence and machine learning to implement a revolutionary change in drug discovery.
The ideal candidate will possess extensive knowledge and skills in the fields of natural language processing (NLP) and large language models (LLMs), including practical problem-solving capabilities of LLMs like GPT-4, Claude, Huggingface, LLaMA, LangChain, LlamaIndex, Pinecone, and more.
You will be well-versed in debugging and adapting ML systems for a variety of scenarios, and you will have a broad interest in machine learning, including parameter-efficient adaptation of large words and vision models. By considering notions such as production-grade machine learning systems, extended context text summarization, and so forth.
To summarize, the candidate will possess expertise in Transformers, API wrapper evaluation (e.g., Auto-GPT and LangChain), semantic search, MLOps, and embedding-based fine refining of natural language processing (NLP) models, including those utilized in Sentence Transformers.
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Details of AI Engineer Jobs in UK with Visa Sponsorship:
| Job Title: | AI Engineer Jobs in UK with Visa Sponsorship |
| Job Type: | Full-Time |
| Salary: | £50,000 – £55,000 / year |
| Experience: | 5 Year |
| Gender: | Both |
| Qualification: | Associate Degree |
| Career Level: | Executive |
| Country: | United Kingdom |
Benefits of AI Engineer Jobs:
- High Demand: AI is one of the most rapidly expanding disciplines, and there is a growing need for specialists in the development, deployment, and maintenance of AI systems. Companies in the technology, healthcare, finance, and manufacturing industries, among others, compete for AI engineers to implement AI for efficiency and innovation.
- Competitive Salary: AI engineers earn competitive salaries owing to the high demand for their specialized expertise and the correspondingly high skill set. AI engineer salaries frequently exceed those of software engineering professionals in other fields, an indication of the significance of AI in influencing business results.
- Diverse Opportunities: AI engineers have the opportunity to participate in a wide range of initiatives, including computer vision, machine learning, robotics, natural language processing, and more. This diversity permits engineers to specialize in niche domains and investigate various areas of interest.
- Innovation: The prospect of collaborating on state-of-the-art technologies and making significant contributions to pioneering innovations presents itself to AI engineers. Artificial intelligence engineers are instrumental in expanding the limits of possibility through the development of medical diagnosis systems, personalized recommendation algorithms, and autonomous vehicles.
- Problem-Solving: The field of AI engineering entails addressing intricate challenges and devising inventive resolutions. Engineers not only develop algorithms and optimize performance but also address ethical concerns and data bias. This fosters problem-solving, critical thinking, and creativity.
- Interdisciplinary Collaboration: Domain-specific domains, such as finance or healthcare, as well as computer science, statistics, and mathematics, are frequently required to collaborate on AI initiatives. The prospect of collaborating with heterogeneous groups presents AI engineers with the opportunity to learn from specialists in various domains and contribute their unique insights to cross-disciplinary undertakings.
- Remote Work Opportunities: A considerable number of AI engineering positions provide the advantage of remote work, enabling engineers to maintain a healthy work-life balance while collaborating with teams worldwide. Remote work opportunities may hold significant appeal for individuals who value professional flexibility and independence.
- Career Growth: Prosperity for Progression in the Workplace Leadership positions, specialized fields, and transitions to academia and research present AI engineers with remarkable avenues for professional development. Ongoing education and awareness of the most recent advancements in artificial intelligence (AI) technologies are imperative for professional development in this ever-evolving domain.
- Global Impact: Artificial intelligence (AI) possesses the capacity to tackle a multitude of urgent global issues, including but not limited to poverty alleviation, climate change, healthcare, and education. AI engineers possess the potential to effectuate a significant societal transformation through the creation of AI solutions that enhance human life and propel constructive developments.
- Job Satisfaction: AI professionals can find immense motivation in contributing to groundbreaking initiatives, resolving complex dilemmas, and witnessing the tangible results of AI implementations. The opportunity to work on intellectually stimulating projects that have the potential to revolutionize industries and enhance human welfare frequently contributes to job satisfaction in AI engineering.
You’ll need:
- MSc/PhD in AI/Machine Learning, Textual Analysis/Natural Language Processing, or Transformer Technology/Large Language Models; preferably post-doctoral or comparable experience.
- Knowledge of LLaMA, LangChain, LlamaIndex, Pinecone, GPT-4, Claude, Huggingface, and LLaMA, in addition to NLP and large language models.
- A proven track record of contributions to significant software and data engineering projects in the AI domain that are related to the life sciences, preferably in the context of drug development and biotechnology startups.
- A comprehensive understanding of cloud computing environments is required, with an exclusive focus on Amazon Web Services.
- Gravity, self-awareness, intuition, leadership prowess by nature, and excellent listening abilities
Knowledge of several of the following will be beneficial:
- The application of AI/ML to challenges in the life sciences.
- Engineering and data solutions for the design and implementation of bioinformatic workflows, with an emphasis on ML/AI applications.
- Gaining insight into methodologies employed in the administration of extensive scientific data collections.
- Proficient programming in Python, Java, C/C++, or R with Machine Learning/Deep Learning Frameworks and SOA NLP APIs
- Proficiency in converting user requirements into process designs and specifications.
- Expertise in enhancing and developing data processing pipelines, Nextflow, and Nextflow Tower; knowledge of SQL and NoSQL; familiarity with graph databases
- Having expertise in network science and advanced statistical methods would be an enormous asset.
You will be among a select group of exceptionally talented AI scientists and engineers who are integrated into an extraordinary, problem-solving technological team of international caliber. The aforementioned group will undertake an unprecedented endeavor to develop and implement AI-powered innovations that will aid in the execution of siRNA and computational drug discovery platforms of the next generation.
Some of the wider benefits:
A substantial discretionary bonus, a highly competitive income, a BUPA for oneself and one’s companion or family, and a 10% employer pension contribution. Candidates domiciled in the United Kingdom who can work four days per week from the West London office may qualify for visa sponsorship.
How To Apply For AI Engineer Jobs in UK with Visa Sponsorship?
If you wish to enroll, please visit the link provided.
Frequently Asked Questions:
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How can I get sponsored for a UK visa?
To obtain a sponsorship license, UK companies must meet the following criteria: Genuine Business Requirements: The UK employer must prove that there’s a genuine need for the migrant worker and that the job offer aligns with the skill level of the visa route.
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How much do AI engineers earn in the UK?
The average salary for an AI engineer is £55,999 per year in the United Kingdom. The average additional cash compensation for an AI engineer in the United Kingdom is £4,167, with a range from £1,945 to £8,928.
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How do I become an AI engineer in the UK?
However, with the right training, practice, and dedication, anyone can learn and become proficient in AI engineering. It requires a strong foundation in computer science, knowledge of machine learning algorithms, proficiency in programming languages like Python, and experience in data management and analysis.
