Company Description V-OptimAIse aims to leverage AI/ML advancements to reduce carbon footprint in steel manufacturing by developing self-learning predictive and diagnostic tools. Our team utilizes under-utilized data to identify production bottlenecks, detect product anomalies, and avoid critical failures. These efforts are geared towards maximizing productivity and improving operational efficiency in steel manufacturing. Role Description This is a part-time remote role for a Senior Machine Learning Engineer specialized in Timeseries Analysis. The Senior Machine Learning Engineer will be responsible for developing and implementing machine learning models for prediction, anomaly detection and non-linear optimisation. Daily tasks also include analyzing timeseries data, optimizing algorithms, and collaborating with cross-functional teams. Also involves developing GenAI tools and leveraging Agentic AI. Qualifications Expertise in timeseries analysis Gaussian Processes (or VGPs), TCNN, VAE etc Python for data analysis, model development GPflow, PyTorch, Bayesian optimisation techniques GenAI and Agents designing Strong foundation in Computer Science and Algorithms Proficiency in Statistics and Data Analysis Excellent problem-solving and critical thinking skills Ability to work independently and remotely Experience in AI/ML applications in manufacturing is a plus Masters or advanced degree in Computer Science, or related field
Company Description V-OptimAIse leverages AI/ML advancements to reduce the carbon footprint in steel manufacturing by developing self-learning predictive and diagnostic tools. Our solutions utilize under-utilised data to identify production bottlenecks, detect product anomalies, and avoid critical failures. These initiatives aim to maximize productivity and improve operational efficiency in steel production. About the Role We are seeking a hands-on Implementation Engineer to join our team. This role involves on-site installation, product-development, commissioning, and integration of IIoT and Industrial Automation systems. You will work with Single Board Computers, Sensors , PLC, SCADA, wiring, and device integration , while also applying basic coding for automation tasks - done mostly using Python. This is a great opportunity for freshers and early-career engineers who are eager to learn and grow in the field of IIoT and Industrial Automation. Key Responsibilities Support on-site implementation, installation, and commissioning of projects. Assist in wiring, device setup, and troubleshooting . Learn and configure SBC & different kinds of sensors , PLC & SCADA systems . Apply basic coding (Python) for automation. Work with project teams to ensure smooth execution. Document activities and provide support during project delivery. Stay curious and up to date with new technologies . Qualifications & Skills Diploma / Bachelor’s in Electrical, Electronics, or Instrumentation Engineering . Freshers or candidates with up to 2 years’ experience in IoT / PLC / SCADA / Industrial Automation. Interest or basic knowledge of industrial protocols (Modbus, MQTT, OPC, node-red). Basic understanding of coding (Python). Strong problem-solving, communication, and learning attitude. What We Offer Opportunity to work on real-world IIoT & automation projects . On-site exposure and practical learning experience. A growth-driven environment to develop technical skills .
Important Details This is Remote Part-Time role and we expect around 12-16 hours of work per week. At times requires travel to client location - costs reimbursed (at max once per month). Pay per month ranges from 40k to 60k (fully based on expertise how well you complete tasks, not experience) Contract shall be at least for 6months. We are indeed looking for long-term collaboration. Hence can be made full time. You should have done: Timeseries Analysis (linear & non-linear), Optimisation (gradient-based and gradient-free), Gaussian Process Regression. (GenAI expertise is a plus). You should be keen about technology, self-disciplined (work with minimal monitoring), take initiatives to help build the product. Company Description V-OptimAIse aims to leverage AI/ML advancements to reduce carbon footprint in steel manufacturing by developing self-learning predictive and diagnostic tools. Our team utilizes under-utilized data to identify production bottlenecks, detect product anomalies, and avoid critical failures. These efforts are geared towards maximizing productivity and improving operational efficiency in steel manufacturing. Role Description This is a part-time remote role for a Senior Machine Learning Engineer specialized in Timeseries Analysis & Generative AI. The Senior Machine Learning Engineer will be responsible for developing and implementing machine learning models for prediction, anomaly detection and non-linear optimisation. Further they develop GenAI tools for providing valid recommendations based on the model output. Daily tasks also include analyzing timeseries data, optimizing algorithms, building GenAI tools capable of helping industrial operators and collaborating with cross-functional teams, developing web-apps based in Streamlit. Also involves developing GenAI tools and leveraging Agentic AI over the app. Qualifications Expertise in timeseries analysis Strong experience applying GenAI, LLMs and Agentic AI for product based platforms Gaussian Processes (or VGPs), TCNN, VAE etc Python for data analysis, model development GPflow, PyTorch, Bayesian optimisation techniques Strong foundation in Computer Science and Algorithms Proficiency in Statistics and Data Analysis Excellent problem-solving and critical thinking skills Ability to work independently and remotely Experience in AI/ML applications in manufacturing is a plus Masters or advanced degree in Computer Science, or related field