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Fractal Analytics
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AI Research Scientist - Foundation Models/Agent/Reinforcement Learning

AI Research Scientist - Foundation Models/Agent/Reinforcement Learning

Fractal Analytics

2 - 6 years

15 - 20 Lacs

Mumbai Pune Chennai Gurugram Bengaluru

Posted:1 week ago| Platform:

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Skills Required

Training Computer vision deep learning Architecture Author Deployment Research Open source Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

Job Location: Bangalore, Pune, Mumbai, Gurgaon, Chennai

Job 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.

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AI Research Scientist - Foundation Models/Agent/Reinforcement Learning