ABOUT THIS FEATURED OPPORTUNITY

The Machine Learning Engineer will join the team to automate and scale the validation of device setup workflows across the channel store environments. You’ll play a critical role in developing intelligent systems that can interpret images, metadata, and contextual signals to determine if the store is complying with standards through visual signals.

THE OPPORTUNITY FOR YOU

• Design and deploy robust computer vision pipelines for real-world, production-scale use cases
• Independently design and execute experiments to validate model assumptions and improve accuracy
• Perform root cause analysis on model failures, and translate findings into concrete improvements
• Integrate Vision-Language Models (VLMs) to enable context-aware image understanding
• Prototype agent-based reasoning flows to surface insights and recommendations from visual signals
• Own and iterate on NLP + CV systems that power internal tools and customer-facing technologies
• Partner cross-functionally with backend, product, and business teams to scale your solutions worldwide
• Translate product goals into practical CV architectures and roadmap milestones
• Contribute to the future vision of AI-powered sales and operational tools
• Seeking a self-driven and accountable professional, with a track record of incorporating feedback and delivering results independently
• Solid knowledge of multimodal reasoning — not just prompting models, but systematically evaluating workflows with LLMs and VLMs together
• Experience with state-of-the-art CVML, including VLMs, multimodal LLMs, and agentic workflows
• Hands-on experience with Vision-Language Models (e.g., CLIP, BLIP, Flamingo, Gemini) with awareness of their strengths, weaknesses, and real-world limitations
• Proven ability to run experiments end-to-end: from hypothesis, to design, to execution, to iteration
• Demonstrated skill in root cause analysis for model misclassifications and system-level failures

Please refer the Job description for details