Posted Apr 25, 2026
As a Senior ML Engineer at Automated Learning Platform, your role will involve the following key responsibilities:
Work closely with Product, Design, Content, and Engineering teams to deeply understand student problems and integrate AI features into the product end-to-end. - Conduct hands-on research and experimentation to identify the best approach for model selection, prompting, evaluation, iteration, and rapid learning. - Develop and enhance AI systems for real learning workflows such as numerical problem solving, image-to-text extraction, and AI-powered content/lecture generation. - Debug, optimize, and enhance the performance of AI systems in terms of accuracy, latency, and cost, while maintaining robust evaluation and testing pipelines to ensure scalability and reliability. - Take ownership of outcomes and strive for impactful and innovative work that revolutionizes the learning experience for students. Qualifications required for this role include:
34 years of practical experience in building and deploying AI solutions, with a strong focus on LLMs/GenAI and expertise in prompting, tool/function calling, RAG, or similar approaches, and evaluation. - Proficiency in Python and production engineering, with the ability to develop scalable APIs/services using FastAPI/Django/Flask, and solid experience with ML stacks like PyTorch, TensorFlow, Scikit-learn, Keras, Hugging Face, and supporting pipelines/scripts. - In-depth knowledge of the ML lifecycle and multimodal exposure, with a strong emphasis on prompt, evaluate, iterate, improve, focusing on accuracy and robustness across text, image, audio, and video domains. Experience with tools like ElevenLabs, Wav2Lip, Manim, AI4Bharat will be advantageous. - A builder mindset with a collaborative approach, adept at problem-solving in ambiguous scenarios, strong experimentation skills, and clear communication to align technical decisions with product outcomes. As a Senior ML Engineer at Automated Learning Platform, your role will involve the following key responsibilities:
Work closely with Product, Design, Content, and Engineering teams to deeply understand student problems and integrate AI features into the product end-to-end. - Conduct hands-on research and experimentation to identify the best approach for model selection, prompting, evaluation, iteration, and rapid learning. - Develop and enhance AI systems for real learning workflows such as numerical problem solving, image-to-text extraction, and AI-powered content/lecture generation. - Debug, optimize, and enhance the performance of AI systems in terms of accuracy, latency, and cost, while maintaining robust evaluation and testing pipelines to ensure scalability and reliability. - Take ownership of outcomes and strive for impactful and innovative work that revolutionizes the learning experience for students. Qualifications required for this role include:
34 years of practical experience in building and deploying AI solutions, with a strong focus on LLMs/GenAI and expertise in prompting, tool/function calling, RAG, or similar approaches, and evaluation. - Proficiency in Python and production engineering, with the ability to develop scalable APIs/services using FastAPI/Django/Flask, and solid experience with ML stacks like PyTorch, TensorFlow, Scikit-learn, Keras, Hugging Face, and supporting pipelines/scripts. - In-depth knowledge of the ML lifecycle and multimodal exposure, with a strong emphasis on prompt, evaluate, iterate, improve, focusing on accuracy and robustness across text, image, audio, and video domains. Experience with tools like ElevenLabs, Wav2Lip, Manim, AI4Bharat will be advantageous. - A builder mindset with a collaborative approach, adept at problem-solving in ambiguous scenarios, strong experimentation skills, and clear communication to align technical decisions with product outcomes.
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