5 Controlnet Jobs

Job Summary: We are seeking a visionary and hands-on AI Architect with 8+ years of experience in designing and deploying AI-driven systems, including Generative AI (GenAI), LLM integration, computer vision, and agentic workflows. This role demands deep technical expertise in transformer models, PyTorch, and tools such as Stable Diffusion, ControlNet, and LangChain, as well as a strong grasp of dataset strategy, bias mitigation, and scalable AI system architecture. Experience with e-commerce or fashion datasets is a strong plus. Key Responsibilities: Architect and lead the development of AI/ML systems, with a focus on Generative AI, including diffusion models, GANs, and LLMs. Implement and optimize models such as Stable Diffusion, ControlNet, and OpenPose for real-world use cases in visual content generation. Design LLM-integrated solutions using LangChain, agentic workflows, and multimodal AI systems. Collaborate with cross-functional teams to define dataset strategy, ensuring data relevance, diversity, and quality. Integrate Hugging Face Transformers and PyTorch-based architectures into production environments. Define and implement best practices around bias & fairness, model explainability, and ethical AI design. Lead architectural decisions for scalable AI platforms, focusing on performance, reliability, and continuous learning capabilities. Leverage domain knowledge in e-commerce/fashion for visual understanding, recommendation, or personalization solutions. Qualifications: 8+ years of experience in AI/ML system architecture, including 3+ years specifically in Generative AI and LLM ecosystems. Proficiency in PyTorch, Transformers, Hugging Face, and LangChain. Deep understanding of diffusion models, GANs, ControlNet, and OpenPose. Experience in designing agentic AI workflows, real-time inference systems, and production-grade AI infrastructure. Proven track record in dataset creation/curation, bias analysis, and fairness optimization. Strong communication skills and the ability to translate complex AI concepts into business impact. Preferred Qualifications : Prior experience with e-commerce, fashion technology, or retail-based AI datasets. Contributions to open-source AI frameworks or publications in relevant research areas. Familiarity with cloud AI services (e.g., AWS Sagemaker, Azure AI, or GCP Vertex AI). Understanding of AI observability, versioning, and model governance. Location - Pan India, Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune.

Job Title: AI / ML Engineer Company: Mukesh Buildtech (Stealth Startup) Work Location: Salem, Tamil Nadu About Us: Mukesh Buildtech is an innovative stealth startup focused on a new marketplace. We are building a cutting-edge platform that leverages advanced technologies to provide unparalleled user experiences. Join our dynamic team and be a part of our exciting journey from the ground up. If you're interested, please send your updated CV to sumathi@mukeshassociates.com. Role Overview: We are seeking a highly skilled Computer Vision & Machine Learning Engineer with expertise in AI-driven image recognition, object detection, and model deployment . The ideal candidate will have experience working with Stable Diffusion, SDXL, ControlNet, and LoRA models for advanced image generation, along with a solid background in TensorFlow, PyTorch, and OpenCV . You will be responsible for fine-tuning models, integrating AI-driven image-processing workflows, and deploying them at scale. Key Responsibilities: Develop and fine-tune Stable Diffusion, SDXL, ControlNet, LoRA models for computer vision applications. Implement inpainting, outpainting, and style transfer techniques to enhance image processing capabilities. Dynamically load LoRA adapters to optimize AI-generated content workflows. Deploy and maintain Inference APIs that trigger backend processes and return image blobs efficiently. Utilize Real-ESRGAN, SwinIR, and other upscaling models to improve image resolution and output quality. Integrate safety checkers to filter out NSFW/violent content within AI-generated images. Optimize GPU scheduling to ensure efficient routing of requests to available GPU workers. Implement model caching strategies to reduce unnecessary reloads and improve inference speed. Work with SQL and NoSQL databases to handle large-scale datasets for training and inference. Collaborate with cross-functional teams to develop and integrate AI models into production environments. Deploy models using cloud services (AWS, Azure, Google Cloud) and containerization tools such as Docker and Kubernetes . Maintain and improve CI/CD pipelines , version control ( Git ), and best practices for model deployment. Adapt pre-trained LLMs for image and product identification applications . Required Skills & Qualifications: 2+ years of experience in Computer Vision, Image Recognition, and Machine Learning . Proficiency in Python , including libraries such as NumPy, OpenCV, and scikit-image . Strong expertise with TensorFlow, PyTorch, or Keras for deep learning model development. Experience working on product identification projects or similar AI-driven applications. Hands-on experience with fine-tuning deep learning models for optimized performance. Understanding of REST and GraphQL APIs for backend AI model integration. Knowledge of database management (SQL & NoSQL) for dataset processing. Familiarity with cloud platforms (AWS, Azure, Google Cloud) for model deployment. Expertise in Docker & Kubernetes for scalable AI systems. Strong grasp of Git, CI/CD pipelines , and software development best practices . Why Join Us: Be a part of a pioneering team at the forefront of marketplace innovation. Work in a collaborative and dynamic environment with opportunities for growth. Contribute to a product that will have a significant impact on the industry.

The controls engineers are responsible for designing, programming, commissioning, and testing of the Material Handling Systems that we are supplying. The controls engineers work closely together with the Project manager, Project Lead and with the mechanical and hardware engineers during the execution process. The controls engineer reports to the Manager Engineering. Job Description & Skill Requirement: Bachelors in electrical /Instrumentation / Control / Electronics. 3+ years of relevant experience inautomationengineering on PLCs (Rockwell-Control Logix, Compact Logix). Good field exposure and ability to troubleshoot systems, instruments and attend shutdown activities. Hands on experience in designing, execution & selection of industrialautomationproducts such as PLC/DCS, VFD, HMI/SCADA, Panel Design, Industrial communication (Ethernet, Profibus, ControlNet, Modbus.) Should have gone through complete project life cycle from design phase to commissioning. Knowledge of AB Hardware & Quality Management Systems & Review. Proficient in handling Customer on technical levels. Proficient to multi-task to handle multiple tasks and guide Project Engineers. Required Rockwell/ Siemens/PLC hardware selection and programming knowledge. Ability to work independently. Outstanding verbal and written communications skills. Responsible for the PLC software within our Material Handling Systems. Ability to analyze the problem and provide solutions during the trouble shooting situations. Help create Engineering work processes. Responsible for the control systems execution, from software design, system design, network design, commissioning, and testing / validation. Know, interpret, and apply procedures, standards, and regulations. Sets independently controls systems in operation according to commissioning plan in consultation with the site supervisor and project controls leader. Report progress to the Controls Project Leader and Manager Engineering. Support of the Electrical Supervisor, and/or Electrical Controls Engineer to minimize potential problems. Communicate and work closely with other groups within VI and project team (i.e., mechanical engineering, project management, supply chain, sales/proposal department and installation). Initiate improvement actions. Drive, support, promote and improve software standardization platform. Develops new modules for the platform. This position requires occasional on-call after-hours support. Travel up to 50%.

Job Summary: We are seeking a visionary and hands-on AI Architect with 8+ years of experience in designing and deploying AI-driven systems, including Generative AI (GenAI), LLM integration, computer vision, and agentic workflows. This role demands deep technical expertise in transformer models, PyTorch, and tools such as Stable Diffusion, ControlNet, and LangChain, as well as a strong grasp of dataset strategy, bias mitigation, and scalable AI system architecture. Experience with e-commerce or fashion datasets is a strong plus. Key Responsibilities: Architect and lead the development of AI/ML systems, with a focus on Generative AI, including diffusion models, GANs, and LLMs. Implement and optimize models such as Stable Diffusion, ControlNet, and OpenPose for real-world use cases in visual content generation. Design LLM-integrated solutions using LangChain, agentic workflows, and multimodal AI systems. Collaborate with cross-functional teams to define dataset strategy, ensuring data relevance, diversity, and quality. Integrate Hugging Face Transformers and PyTorch-based architectures into production environments. Define and implement best practices around bias & fairness, model explainability, and ethical AI design. Lead architectural decisions for scalable AI platforms, focusing on performance, reliability, and continuous learning capabilities. Leverage domain knowledge in e-commerce/fashion for visual understanding, recommendation, or personalization solutions. Qualifications: 8+ years of experience in AI/ML system architecture, including 3+ years specifically in Generative AI and LLM ecosystems. Proficiency in PyTorch, Transformers, Hugging Face, and LangChain. Deep understanding of diffusion models, GANs, ControlNet, and OpenPose. Experience in designing agentic AI workflows, real-time inference systems, and production-grade AI infrastructure. Proven track record in dataset creation/curation, bias analysis, and fairness optimization. Strong communication skills and the ability to translate complex AI concepts into business impact. Preferred Qualifications : Prior experience with e-commerce, fashion technology, or retail-based AI datasets. Contributions to open-source AI frameworks or publications in relevant research areas. Familiarity with cloud AI services (e.g., AWS Sagemaker, Azure AI, or GCP Vertex AI). Understanding of AI observability, versioning, and model governance. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Experience in the design and implementation of new and/or existing PLC, based process control systems. Experience with industrial communications networks, such as Ethernet/IP, Fiber optic systems, Modbus RTU, Modbus TCP, ControlNet, DNP3.0. and/or IEC61850. Experience with Rockwell Automation Products hardware and software product suites (ControlLogix, Logix 5000, FT View, FT Historian and FT VantagePoint.) experience. Experience with object oriented based control system design methods. Control System Architecture Design (Client Server); including Virtual Client Server design experience preferred Proven abilities in design, engineering, start up, testing, and implementation phases of projects Review Specifications, IC Control drawings, HMI screens, PLC programs, SCADA, etc. Requires understanding and knowledge process instrumentation such as flow, level, pressure, and temperature instruments. Knowledge of Industry standard proves design methods such as ISA and UL 508A with technical/engineering controls background. Knowledge of current electrical safety standards such as NEC and OHSA Experience in hardware design of process control systems including control panel design including heat load calculations, power/load calculation, and circuit protection. Experience in process control discrete and analog signals for DCS/PLC based systems including hardware design, hardware testing, troubleshooting and implementation