AI Research Engineer/Scientist – Reinforced Learning Full Time

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JD – AI Research Scientist

About The Company

About Fractal and its vision to become a leader in AI research

Job Overview

We are looking for people who can explore new ideas, design and implement next-generation architectures/techniques in image/video, language, audio and multimodal space. You should be motivated to push the boundaries not just in state-of-the-art performance, but also in balancing performance in terms of inference speed and compute resource usage. You will collaborate with a multidisciplinary team of researchers, engineers, and data scientists to develop and deploy practical and scalable solutions to real-world challenges in areas such as domain based instruction fine-tuning LLMs, improving text to image and foundational models, to name a few. Your work will have a direct impact on the development of our AI-driven products and services.

Responsibilities

• Conduct research and stay up to date with the latest advancements in computer vision, NLP, deep learning, RL and related fields.
• Design and develop novel and next generation of deep learning algorithms, models, and techniques to address specific problem domains
• Document research findings, methodologies, and experimental results in technical reports, blogs and papers.
• Publish research findings and contribute to conferences, workshops, and other scientific forums.
• Collaborate with engineering and business teams on model deployment and customised training respectively.

Qualifications

• Extensive understanding of advanced DL or generative architectures/techniques like diffusion architectures, attention models, LLMs, SAM, RLHF etc
• Have a track record of coming up with new ideas or improving upon existing ideas in deep learning quickly, demonstrated by accomplishments such as first author publications or published/deployed projects or impactful blogs.
• Ability to efficiently work on a modern deep learning stack, such as Python, PyTorch, and GPU-enabled compute, eg writing non-trivial custom architecture in Pytorch.
• Ability to iterate quickly on open-source code-bases with attention to backwards compatibility, usability, and readability.
• Creative, fast-paced executor, detail-oriented, eager to learn, acquire new skills.
• Ability to work effectively in a collaborative team environment and take ownership.
• Strong belief in a positive-sum game, valuing cooperation and collaboration over zero-sum competition.

If you like wild growth and working with happy, enthusiastic over-achievers, you’ll enjoy your career with us!

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