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.
* 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.
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