sanskar unkule
@sanskarunkule
Prompt Engineer specializing in AI model optimization and data annotation.
What I'm looking for
As a dedicated Prompt Engineer at Zensar Technologies, I have honed my skills in developing and refining prompt structures to enhance AI model accuracy and reliability. My work primarily focuses on advanced language model training and optimization, particularly within NVIDIA’s NeMo project. Collaborating with cross-functional teams, I ensure that our prompts align with project objectives while maintaining the highest standards of output quality.
In addition to my role at Zensar, I freelance as a Prompt Engineer at Outlier.ai, where I engage in diverse projects that leverage Reinforcement Learning with Human Feedback (RLHF) techniques. My contributions include evaluating model-generated responses and refining instruction sets to improve model performance. I take pride in my ability to provide constructive feedback that drives iterative improvements, ensuring our AI models meet user requirements effectively.
Experience
Work history, roles, and key accomplishments
Prompt Engineer
Zensar Technologies
Oct 2023 - Present (1 year 7 months)
As a Prompt Engineer at Zensar Technologies, I developed and refined prompt structures to enhance AI model accuracy, focusing on advanced language model training for NVIDIA's NeMo project. I collaborated with cross-functional teams to customize prompts and generated dense captions for video data, contributing to chatbot creation planning.
In my freelance role at Outlier.ai, I worked on various projects applying Reinforcement Learning with Human Feedback (RLHF) techniques. I evaluated model-generated responses, refined instruction sets, and contributed to fine-tuning models to enhance performance and alignment with project objectives.
Education
Degrees, certifications, and relevant coursework
SIES Graduate School of Technology
Bachelor of Engineering, Computer Engineering
2020 - 2024
Grade: 9.3
Pursued a Bachelor of Engineering in Computer Engineering, focusing on the principles of computer science and engineering. Achieved a grade of 9.3, demonstrating a strong understanding of engineering concepts and applications.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Social media
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