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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** RJ Brands LLC - **Location:** Mahwah, NJ, United States - **Salary:** $140,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Automated Storage and Retrieval Systems, Microsoft Azure, Data Cleansing, Software Debugging, Memory Management, Linux on Embedded Systems, Firmware, Monitoring of Systems, High-Level Architecture, Python (Programming Language), Machine Learning, Language Modeling, Object Detection, Recommender Systems, Tensorflow, Search Technologies, Smart Devices, Visual Systems, Google Cloud, Pytorch, Large Language Models, Deep Learning, Generative AI, Low Latency, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, TensorRT, Virtual Agents - **Published:** June 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=629a6ffa6c8fe733 ## About the Role Do you have experience in System deployment?, * Experience developing and deploying machine learning models in production environments. * Strong experience with computer vision, image classification, object detection, deep learning, or related machine learning applications. * Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, or similar technologies. * Experience building and managing datasets used for machine learning model development. * Experience deploying or optimizing models for embedded systems, edge devices, or resource-constrained environments. * Experience working with public cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, including their machine learning and AI services. * Experience with multimodal foundation models, vision-language models (VLMs), or other AI systems that combine vision, language, and contextual understanding. * Experience with MLOps practices including model lifecycle management, experiment tracking, model monitoring, and CI/CD pipelines for machine learning systems. * Understanding of model optimization techniques such as quantization, pruning, and inference acceleration. * Ability to independently evaluate new technologies, research, and model architectures. * Strong analytical, problem-solving, and debugging skills. * Excellent communication and cross-functional collaboration skills. Preferred Qualifications * Experience with embedded Linux, ARM-based platforms, or edge AI hardware. * Experience with TensorFlow Lite, ONNX Runtime, OpenVINO, TensorRT, or similar deployment frameworks. * Experience with connected consumer products, IoT devices, robotics, or embedded vision systems. * Experience with large language models (LLMs), small language models (SLMs), vision-language models (VLMs), generative AI, recommendation systems, agentic AI systems, or AI-powered user experiences. * Experience with retrieval-augmented generation (RAG), vector databases, embeddings, semantic search, or knowledge retrieval systems. * Experience designing AI agents capable of monitoring, planning, reasoning, and decision-making using vision, sensor, and contextual data. * Experience with AWS machine learning and AI services preferred. ## Description * Design, train, and deploy machine learning and computer vision models that power autonomous cooking experiences within CHEF iQ products. * Develop image classification, object detection, and state-recognition models that identify food types, cooking progress, doneness levels, and other key inputs used to guide cooking decisions. * Build and manage datasets, including data collection, labeling, preparation, augmentation, and validation. * Own the full machine learning lifecycle, from data preparation and model training through deployment, monitoring, and continuous improvement. * Research, evaluate, and apply emerging machine learning techniques, including computer vision, generative AI, large language models (LLMs), vision-language models (VLMs), multimodal AI, and academic research, to improve product performance and customer experiences. * Deploy and optimize models for cloud and edge devices, balancing accuracy, latency, memory usage, power consumption, and overall system performance. * Collaborate with firmware, software, hardware, and product teams to integrate machine learning capabilities into consumer products. * Develop systems that combine vision, sensor, and contextual data to enable intelligent recommendations and autonomous next-step actions. * Design and develop AI-driven systems that combine perception, reasoning, and decision-making capabilities to enable intelligent and autonomous cooking experiences. * Establish testing methodologies and performance metrics to validate models across real-world usage scenarios. * Document model architectures, experiments, and deployment approaches. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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