Job Title: Data Scientist Industrial AI Location: Bengaluru, India (On-site/Hybrid) Department: AI & Digital Twins About Giniminds Virtual AI Factory Giniminds is pioneering the future of manufacturing with its Virtual AI Factory— a cutting-edge, photorealistic digital twin of real-world production environments. Built on NVIDIA Omniverse, it integrates simulation, AI, and real time sensor data to enable predictive analytics, process optimization, and accelerated production cycles. This platform serves as a risk-free innovation hub to develop, validate, and deploy AI solutions. Position Summary We are seeking a Digital Twin Developer specializing in NVIDIA Omniverse and Industrial AI. You will design, build, and simulate digital replicas of manufacturing operations, integrating real-world data, 3D visualization, and AI driven insights to solve complex industrial challenges such as predictive maintenance, process efficiency, and defect detection. Key Responsibilities Develop advanced digital twin environments using Omniverse USD Composer and Universal Scene Description (USD)workflows. Import, optimize, and manage complex 3D CAD assets from tools such as Siemens NX, SolidWorks, and AutoCAD for real-time factory simulations. Implement physics-based simulations for robotic systems, material flow, and machinery using PhysX and Isaac Sim. Integrate AI/ML models for predictive maintenance (RNN, LSTM) and visual defect detection (CNN, Transformers). Generate synthetic datasets for AI training using Omniverse Replicator and other tools, including artificial sensor and image data. Collaborate with data engineering teams to connect the digital twin to live factory data via MQTT, Kafka, OPC-UA, and industrial systems (MES, ERP, PLM). Develop custom dashboards and visualization tools within Omniverse for monitoring KPIs, alerts, and simulation outputs. Required Skills & Qualifications Strong hands-on experience with NVIDIA Omniverse (USD Composer, Nucleus). Proficiency in 3D asset management using Blender, Maya, or 3ds Max. Experience with NVIDIA PhysX and/or Isaac Sim for industrial robotics and process simulations. Practical experience in industrial AI model development, including vision based inspection or predictive analytics. Advanced programming skills in Python for Omniverse scripting, simulation automation, and tool development. Solid understanding of manufacturing processes, MES/ERP systems, and factory operations. Preferred Qualifications Experience with synthetic data generation tools (Omniverse Replicator, GANs, Diffusion Models). In-depth knowledge of USD workflows, including layering and composition arcs. Familiarity with industrial data streaming tools (Kafka, MQTT). Cloud computing and DevOps exposure AWS, Azure, GCP, Docker). Experience in developing Omniverse extensions or custom applications. What We Offer Opportunity to work on groundbreaking AI + industrial automation projects. Competitive salary and comprehensive benefits. Access to advanced tools, NVIDIA technology, and high-performance hardware. Dynamic, collaborative work culture with a strong focus on innovation and career growth Job Type: Full-time Ability to commute/relocate: JP Nagar, Bengaluru, Karnataka: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience working with Digital Twins? Do you have experience with 3D CAD Tools like Blender, Maya etc ? Do you have experience with tools like Kafka? Do you have experience with Industrial AI Model Development? Education: Bachelor's (Required) Work Location: In person
Job Designation: Data Scientist (LLMs & GenAI) Job Overview: We are looking for an experienced Python developer with a strong background in Large Language Models (LLMs), Generative AI (GenAI), excellent knowledge prompt engineering, tools for RAG development. The ideal candidate will have hands-on experience in prompt engineering, working with advanced AI frameworks such as LlamaIndex, LangChain, LangGraph, and AutoGen. This role involves building scalable applications and solutions that leverage the latest advancements in AI to solve complex business problems like intelligent chatbots, assistants and digital twins. Key Responsibilities: Develop and implement AI-driven solutions using Python and state-of-the-art LLMs like Azure OpenAI, Lama, Gemini. Design and optimize prompt engineering strategies to improve model responses and performance. Work with tools like LlamaIndex, LangChain, and LangGraph to integrate AI into business workflows. Use LangGraph and AutoGen to design and manage multi-step reasoning workflows for complex applications by using poly LLMs. Develop APIs and interfaces for integrating LLM-based models into existing systems on Flask. Perform performance testing, debugging, and continuous improvement of APIs. Research on developing conversational agents, personalized recommendations, and other GenAI-powered products like intelligent chatbots, assistants and digital twins. Keep up with the latest developments in AI/ML and apply new techniques to improve our models and tools. Required Skills & Qualifications: Experience: 2-4 years of Python development experience with a focus on AI/ML. Knowledge: In-depth understanding of LLMs, GenAI, and prompt engineering. Frameworks: Proficiency in LlamaIndex, LangChain, LangGraph, and AutoGen. Machine Learning: Experience with deploying and scaling machine learning models in production environments. Speech processing : Proficiency with speech-to-text or voice recognition systems such as Azure cognitive services and Google Speech API. NLP: Solid understanding of natural language processing, tokenization, and semantic analysis. APIs: Strong experience in developing and integrating RESTful APIs on Flask for AI/ML systems. Problem Solving: Ability to create scalable solutions for multi-modal, poly LLM and generative AI applications. Collaboration: Excellent communication and teamwork skills to collaborate with cross-functional teams. Preferred Qualifications: Knowledge on Speech synthesis and Sentience simulation Experience with cloud platforms (Azure and GCP) for deploying and scaling AI/ML models. Familiarity with containerization (Docker) and orchestration tools (Kubernetes) for deploying microservices. Experience with reinforcement learning, transformers, or other cutting-edge techniques. Understanding of ethical AI, data privacy, and responsible AI practices. Job Type: Full-time Ability to commute/relocate: Bangalore, Karnataka: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Required) Experience: LLM: 2 years (Preferred) LangChain or LangGraph: 2 years (Preferred) Docker: 2 years (Preferred) STT / ASR: 2 years (Preferred) API Development: 2 years (Preferred) Work Location: In person
Job Title: Pre-Sales & Solutioning Engineer – Data Center & Integration Technologies Location: [Gurgaon] Experience: 3+ years Department: Sales Engineering / Solutions Reporting to: Director -Sales About Giniminds: Giniminds is a technology-driven innovation company at the forefront of Digital Transformation, AI, and Enterprise Architecture. We partner with global enterprises to co-create and implement impactful solutions that integrate modern platforms, intelligent infrastructure, and deep domain knowledge. Role Summary: We are looking for a dynamic Pre-Sales & Solutioning Engineer to lead the technical discovery, design, and presentation of integrated infrastructure and data solutions. You will work closely with customers, sales teams, and engineering partners to position Giniminds' server and data center offerings along with advanced integration platforms like Confluent Kafka, StreamSets, and Software AG WebMethods. Key Responsibilities: Pre-Sales Engagement: Participate in customer meetings, understand business needs, and translate them into technical solutions. Prepare and deliver technical presentations, demos, POCs, and RFP responses. * Collaboration: Act as a bridge between sales, product, and engineering teams to align solution offerings with customer expectations. Work with OEM partners (Dell, Cisco, NetApp, Pure Storage, etc.) for sizing, licensing, and compatibility. Client Advisory: Consult customers on infrastructure modernization, integration strategy, and data fabric architecture. Advise on hybrid/multi-cloud deployment strategies, high availability, and failover architectures. * Documentation & Enablement: Create solution blueprints, BOMs, integration workflows, and architecture documents. Support knowledge transfer to internal teams and customers post-deployment. Required Skills & Experience: Infrastructure Expertise: Strong understanding of server platforms, compute virtualization, hyperconverged infrastructure, and data center networking. Experience with Dell PowerEdge, Cisco UCS, HPE servers, and enterprise storage (Pure, NetApp, etc.). Integration Platforms: Exposure with Confluent Kafka (topics, brokers, schema registry, KSQL, connectors). Exposure to StreamSets, WebMethods, or other enterprise integration tools. Presales & Client Facing: Experience in creating RFP/RFI responses, presentations, and POCs. Strong communication and stakeholder engagement skills. Cloud & DevOps (preferred): Knowledge of Kubernetes, container orchestration, CI/CD pipelines. Experience with cloud infrastructure (AWS/GCP/Azure) is a plus. Qualifications: Bachelor's or Master's in Computer Science, Engineering, or related field. 3 + years in IT infrastructure, integration, or pre-sales engineering roles. Certifications in relevant domains (e.g., Cisco DC, VMware, Openshift) are a plus. Why Join Giniminds? Work on cutting-edge digital transformation programs across industries. Be part of a collaborative, innovation-led team. Opportunities to work with global partners in cloud, data, and AI ecosystems. Job Type: Full-time Pay: ₹1,100,000.00 - ₹1,200,000.00 per year Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Experience: Pre sales : 3 years (Required) Solution engineering: 3 years (Required) IT Infrastructure : 3 years (Required) Integration: 3 years (Required) Work Location: In person