At a Glance
- Tasks: Design and develop cutting-edge AI models, focusing on Large Language Models.
- Company: AGITProp is an innovative AI-driven quantitative research firm pushing the boundaries of advanced modelling.
- Benefits: Enjoy a collaborative culture, mentorship opportunities, and the chance to work with top tech and finance minds.
- Why this job: Join a dynamic team at the forefront of AI research, making impactful contributions in finance.
- Qualifications: Master's degree in a relevant field; 5+ years in AI research or engineering, especially with LLMs.
- Other info: We value diversity and are committed to creating an inclusive environment for all.
The predicted salary is between 48000 - 84000 Β£ per year.
AGITProp is an AI-driven quantitative research firm that continues to push the boundaries of advanced modelling, from algorithmic trading to factor modelling and other cutting-edge applications. We harness the latest insights from foundation and large language models (LLMs) to build novel solutions across multiple modalities. Now in our second year, we have ambitious growth plans and are searching for the best and brightest minds from across tech and finance to help us achieve our aim.
We are seeking a highly talented and experienced Senior Research Engineer with a strong background in deep learning, particularly in the development and application of Large Language Models (LLMs), to join our growing team. This role blends research and engineering expertise, requiring a deep understanding of AI/ML principles, strong programming skills, and the ability to contribute to cutting-edge research while also building and deploying practical solutions. Experience in the financial services industry is highly desirable. The successful candidate will collaborate with team members to advance our AI capabilities.
Responsibilities
- Design, develop, implement, and train very large AI models, with a focus on LLMs.
- Conduct original research in deep learning, particularly in areas relevant to LLMs, exploring novel architectures, training processes, and applications within the financial domain.
- Collaborate with portfolio managers, quants, traders, and engineers to understand business needs and translate them into effective AI/ML solutions.
- Build and maintain efficient, scalable, and reliable AI infrastructure, tools, and pipelines to support the development and deployment of machine learning models.
- Stay current with the latest advancements in AI, machine learning, and data science, particularly in the LLM field, and share knowledge with the team.
- Contribute to the creation of AI research pipelines, ensuring high data quality standards, rigorous model validation, and comprehensive performance evaluation.
- Mentor and guide junior engineers and researchers, fostering a culture of innovation and collaboration.
Qualifications
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is preferred.
- Minimum five years of experience in AI research or engineering, with a demonstrable focus on deep learning and LLMs.
- Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry.
- Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques.
- Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus.
- Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical audiences.
- Knowledge of quantitative finance, time series modeling, and trading strategies is highly desirable.
Desired Skills
- Experience with specific LLM architectures (e.g., Transformers, RNNs).
- Familiarity with time series analysis techniques.
- Experience with cloud computing platforms (e.g., AWS, GCP, Azure).
- Strong software engineering skills and experience with version control systems (e.g., Git).
- Ability to work independently and as part of a team.
At AGITProp, we believe AI's strength comes from the diversity of its creators. Weβre dedicated to building an inclusive and welcoming environment where people of all backgrounds and experiences can flourish. We know that a diverse team brings broader perspectives, more innovative solutions, and ultimately, better outcomes.
Contact Detail:
AGITProp Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Research Engineer
β¨Tip Number 1
Familiarise yourself with the latest advancements in Large Language Models (LLMs) and deep learning. Follow key researchers and organisations in the field on social media or through academic publications to stay updated on trends and breakthroughs that could be relevant to AGITProp's work.
β¨Tip Number 2
Engage with the AI and finance communities by attending conferences, webinars, or meetups. Networking with professionals in these fields can provide valuable insights and connections that may help you stand out as a candidate for the Senior Research Engineer position.
β¨Tip Number 3
Showcase your practical experience by working on personal projects or contributing to open-source initiatives related to LLMs and AI in finance. This hands-on experience will not only enhance your skills but also demonstrate your passion and commitment to potential employers.
β¨Tip Number 4
Prepare to discuss your previous work in AI and deep learning during interviews. Be ready to explain your thought process, the challenges you faced, and how you overcame them, particularly in projects that align with AGITProp's focus on financial applications.
We think you need these skills to ace Senior Research Engineer
Some tips for your application π«‘
Tailor Your CV: Make sure your CV highlights your experience in deep learning and LLMs. Include specific projects or roles that demonstrate your expertise in AI/ML, particularly within the financial services sector.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your passion for AI and its applications in finance. Mention how your background aligns with AGITProp's goals and your enthusiasm for contributing to their innovative projects.
Showcase Relevant Projects: If you have worked on any relevant projects, especially those involving LLMs or AI-driven solutions in finance, be sure to include them in your application. Provide details about your role, the technologies used, and the outcomes achieved.
Highlight Collaboration Skills: Since the role involves collaboration with various stakeholders, emphasise your ability to work in teams. Share examples of how you've successfully communicated complex technical ideas to both technical and non-technical audiences.
How to prepare for a job interview at AGITProp
β¨Showcase Your Deep Learning Expertise
Be prepared to discuss your experience with deep learning, particularly in developing and applying Large Language Models (LLMs). Highlight specific projects where you've successfully implemented these technologies, as this will demonstrate your capability to contribute to AGITProp's ambitious goals.
β¨Understand the Financial Context
Since the role is within the financial services industry, brush up on relevant concepts like quantitative finance and trading strategies. Being able to relate your technical skills to real-world financial applications will set you apart from other candidates.
β¨Communicate Complex Ideas Clearly
AGITProp values excellent communication skills. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with both technical and non-technical team members. This skill is crucial for translating business needs into effective AI/ML solutions.
β¨Demonstrate a Collaborative Spirit
Emphasise your ability to work as part of a team. Share examples of how you've collaborated with others in previous roles, especially in mentoring junior engineers or researchers. AGITProp is looking for someone who can foster a culture of innovation and collaboration.