Responsibilities:

<ul>
<li style="margin-left:0px;">Tame the Long Tail: You will develop strategies to detect and handle "rare events" (novel packaging, damaged goods, occlusion) that break traditional detectors.</li>
</ul>

<ul>
<li style="margin-left:0px;">Leverage Foundation Models: You will adapt and fine-tune large-scale foundation models for specific robotic manipulation tasks, toward zero-shot generalization capabilities.</li>
</ul>

<ul>
<li style="margin-left:0px;">Model Optimization: You will take massive, compute-heavy models and distill them into efficient, lightweight networks that can run with low latency on edge compute (NVIDIA Orin).</li>
</ul>

<ul>
<li style="margin-left:0px;">Drive Technical Excellence: As a senior member of the team, you will stay ahead of the curve on CV/ML research, translate relevant breakthroughs into production-grade gestures and mentor junior engineers. </li>
</ul>
Skills:

<ul>
<li style="margin-left:0px;">5+ Years of Experience in Computer Vision and Deep Learning, with a specific focus on applied research or advanced R&amp;D.</li>
</ul>

<ul>
<li style="margin-left:0px;">You have hands-on experience with modern architectures: Transformers (ViT), Self-Supervised Learning (SSL), Vision-Language Models (VLMs), or Zero-Shot detection.</li>
</ul>

<ul>
<li style="margin-left:0px;">Expert-level Python and PyTorch skills.</li>
</ul>

<ul>
<li style="margin-left:0px;">You are focused on the "hard" problems (occlusions, reflective surfaces, and variable lighting), and you know when to use a large model versus a simple heuristic.</li>
</ul>

<ul>
<li>Experience with Model Distillation (Student-Teacher networks) and Quantization.</li>
</ul>

<ul>
<li style="margin-left:0px;">You can demystify complex AI research and articulate performance implications to engineering and product stakeholders.</li>
</ul>

<ul>
<li style="margin-left:0px;">Familiarity with Docker, AWS/GCP (S3, EC2) and experiment tracking tools. </li>
</ul>

Sr Machine Learning Engineer

Responsibilities: Tame the Long Tail: You will develop strategies to detect and handle "rare events" (novel packaging, damaged goods, occlusion) that break traditional detectors. Leverage Foundation Models: You will adapt and fine-tune large-scale foundation models for specific robotic manipulation tasks, toward zero-shot generalization capabilities. Model Optimization: You will take massive, compute-heavy models and distill them into efficient, lightweight networks that can run with low latency on edge compute (NVIDIA Orin). Drive Technical Excellence: As a senior member of the team, you will stay ahead of the curve on CV/ML research, translate relevant breakthroughs into production-grade gestures and mentor junior engineers. Skills: 5+ Years of Experience in Computer Vision and Deep Learning, with a specific focus on applied research or advanced R&amp;D. You have hands-on experience with modern architectures: Transformers (ViT), Self-Supervised Learning (SSL), Vision-Language Models (VLMs), or Zero-Shot detection. Expert-level Python and PyTorch skills. You are focused on the "hard" problems (occlusions, reflective surfaces, and variable lighting), and you know when to use a large model versus a simple heuristic. Experience with Model Distillation (Student-Teacher networks) and Quantization. You can demystify complex AI research and articulate performance implications to engineering and product stakeholders. Familiarity with Docker, AWS/GCP (S3, EC2) and experiment tracking tools.

Sr Machine Learning Engineer in Delhi (UID-16394)

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Job Description for Sr Machine Learning Engineer

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