TORQ ( Mintelligence ) - Sr. AI Scientist
Job Description
Location: Navi Mumbai (CBD Belapur)
Work Mode: 5 Days Work From Office
Experience: 5 – 10 Years
Qualification: B.Tech from (CS/AI/ML/DS/EE preferred)
Company Type: Startup (candidate must be willing to work in a startup environment)
We are looking for a highly skilled Senior AI Scientist who is a subject matter expert in advanced AI/ML model development and research. The ideal candidate should have strong hands-on experience with LLMs, transformers, diffusion models, multimodal architectures , and must be comfortable leading research-driven projects in a fast-paced startup environment.
\nThis role requires deep technical expertise, strong coding abilities, and the ability to review, validate, and debug complex ML codebases.
Key Responsibilities 1. Research & Innovation \n- \n
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Lead research in LLMs, diffusion models, transformers, and multimodal AI systems .
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Explore state-of-the-art literature and implement new ideas, techniques, and architectures.
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Develop prototypes and run experiments for AI model advancement.
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Design, train, fine-tune, and optimize deep learning models.
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Work with large and diverse datasets across text, image, and multimodal domains.
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Deliver production-ready models with high performance and reliability.
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Identify, debug, and resolve coding errors in ML pipelines and model scripts.
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Maintain clean, high-quality research and production code.
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Collaborate closely with engineering teams for smooth integration.
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Perform model benchmarking and statistical evaluations.
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Conduct ablation studies and experiment documentation.
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Present insights and findings with clear technical reasoning.
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Strong research experience in deep learning, NLP, CV, generative AI , or related fields.
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Hands-on expertise with transformers, LLMs, diffusion models, multimodal systems .
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Proficiency in Python , PyTorch / TensorFlow, and modern ML toolkits.
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Ability to debug and optimize large-scale ML systems.
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Strong mathematical foundations and problem-solving skills.
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Willingness to thrive in a fast-paced startup environment.
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Research publications, patents, or open-source contributions.
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Experience with distributed training, GPU optimization, or cloud ML platforms (AWS/GCP/Azure).
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Familiarity with reproducible research tools and ML experimentation frameworks.
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