Job Title

WORK MODE: Full-Time | Hybrid - Bangalore | 3 Days WFO EXPERIENCE: 5+ Years (shipping deep learning models into production)JOB DESCRIPTION: The Role We are seeking a Lead Deep Learning Engineer to lead the development of the company’s Visual AI stack. This is a highly technical Senior Individual Contributor role with strategic ownership. You will work with large-scale, real-world culinary vision data captured from robots operating in homes and convert that data into production-grade perception and autonomy systems. This role requiresmodel inventors and AI architects , not just pipeline optimizers.Key Responsibilities 1. Model Architecture & Native AI Development Design and train transformer-based computer vision models from first principles Develop capabilities across: Segmentation | Object detection | Classification | Regression Work extensively with Vision Transformer architectures such as: ViT | Swin Transformer | MViT | SegFormer Make principled tradeoffs across latency, reliability, cost, and deployed performanceThis role demands hands-on experience building and experimenting with transformer architectures—not merely fine-tuning pre-trained models or integrating APIs2. Autonomy & Model Strategy Define the appropriate autonomy targets given real-world kitchen variability Translate autonomy goals into a clear Operational Design Domain Decide when to use large general models vs. distilled or task-specific models Make strategic shifts based on real-world constraints and deployment learningsThis is not just execution, you will influence core technical direction.3. Data Strategy & Failure-Driven Learning Define what data should be collected and in what sequence Balance on-device data, human demonstrations, and curated datasets Design robust feedback loops using: Intervention data | Edge case logging | Replay and prioritization frameworks Continuously improve reliability in deployed consumer environments4. Cross-Functional Leadership You will collaborate closely with: Data & Annotation teams working on culinary workflows Core Software teams integrating perception models into autonomous cooking systemsYou will lead a highly capable team while remaining deeply hands-on.Ideal Candidate ProfileRequired 5+ years of experience shipping deep learning models into production Deep, hands-on expertise in Vision Transformers Proven experience designing and training models from scratch Strong architectural intuition and first-principles thinking Demonstrated ownership over technical decisions and model directionPreferred Broad computer vision experience across multiple perception domains Experience with real-world, noisy, physical-environment data Background in segmentation, detection, and state-change recognition tasks Comfort operating in ambiguity and defining strategyImportant ClarificationThis isnotprimarily: An ML infrastructure optimization role A DeepStream/TensorRT-heavy deployment engineering position A YOLO-integration or API-centric ML role A RAG/chatbot-focused AI positionWe are specifically looking for engineers who design and invent AI models, not those who primarily scale or deploy them.Why This Opportunity Work on real-world autonomy at consumer scale Direct impact on AI operating in physical environments High ownership and strategic influence Join a mission-driven team building category-defining robotics productsAbout the Company: A well-funded, Series A consumer robotics company building autonomous kitchen robots that cook complete meals in real homes. Their AI-powered systems are deployed at scale in the U.S. market and operate daily in dynamic, real-world kitchen environments. This is one of the few teams globally shipping cutting-edge AI into the physical world at consumer scale.