MSDS Author On-site (Mohali)/Hybrid/Remote| Full-time | 5-10 Yrs Job Summary We're seeking an experienced MSDS Author to join our team. Responsibilities include preparing material safety data sheets assessing product compositions and hazards according to country/region (current profile includes EU, North America including USA and Canada, and China). We prefer candidates who are open to working from the office but also provide skilled individuals with the option for hybrid or fully remote arrangements. Key Responsibilities Independently assess product compositions or chemical formulations to applicable country regulations Research hazards and properties of components to make appropriate MSDS classification for global regulations Determine appropriate Hazard Assessments and MSDS phrases based on the assessment Directly interact with overseas clients to meet their author ing requirements Actively work with other team members to incorporate improvement projects Mentor junior author s in platform utilization and other system/tools Create and format MSDS documents utilizing client suggested MSDS author ing platform Review completed MSDS s Requirements Bachelor's degree in chemistry from a reputed university 5-10 years prior MSDS author ing experience with reputed service providers or MNC chemicals manufacturing companies Strong analytical and English communication skills (written and verbal) Strong understanding of regulations (CLP, OSHA, WHMIS, GHS, 49 CFR, 29 CFR, HazCom, ROHS, Inventories, TDG, etc.) Knowledge of prevalent MSDS author ing software platforms - SAP EH&S and/or MSDgen, WERCS, or similar; Knowledge of extended SDS for ECHA is a plus Understanding of active versus inactive ingredients with respect to physical form, volume, and hazards Preferred Qualifications Good knowledge of MS Office and MS Teams The capability to author all 16 sections of SDS Knowledge of chemical compounds, families, and pharmaceutical products Interested candidates can send resume at tanvir.k@idsil.com

Job Summary We are seeking a forward-thinking AI Architect to design, lead, and scale enterprise-grade AI systems and solutions across domains. This role demands deep expertise in machine learning, generative AI, data engineering, cloud-native architecture, and orchestration frameworks. You will collaborate with cross-functional teams to translate business requirements into intelligent, production-ready AI solutions. Key Responsibilities Architecture & Strategy : Design end-to-end AI architectures that include data pipelines, model development, MLOps, and inference serving. Create scalable, reusable, and modular AI components for different use cases (vision, NLP, time series, etc.). Drive architecture decisions across AI solutions, including multi-modal models, LLMs, and agentic workflows. Ensure interoperability of AI systems across cloud (AWS/GCP/Azure), edge, and hybrid environments. Technical Leadership Guide teams in selecting appropriate models (traditional ML, deep learning, transformers, etc.) and technologies. Lead architectural reviews and ensure compliance with security, performance, and governance policies. Mentor engineering and data science teams in best practices for AI/ML, GenAI, and MLOps. Model Lifecycle & Engineering Oversee implementation of model lifecycle using CI/CD for ML (MLOps) and/or LLMOps workflows. Define architecture for Retrieval Augmented Generation (RAG), vector databases, embeddings, prompt engineering, etc. Design pipelines for fine-tuning, evaluation, monitoring, and retraining of models. Data & Infrastructure Collaborate with data engineers to ensure data quality, feature pipelines, and scalable data stores. Architect systems for synthetic data generation, augmentation, and real-time streaming inputs. Define solutions leveraging data lakes, data warehouses, and graph databases. Client Engagement / Product Integration Interface with business/product stakeholders to align AI strategy with KPIs. Collaborate with DevOps teams to integrate models into products via APIs/microservices. Required Skills & Experience Core Skills : Strong foundation in AI/ML/DL (Scikit-learn, TensorFlow, PyTorch, Transformers, Langchain, etc.) Advanced knowledge of Generative AI (LLMs, diffusion models, multimodal models, etc.) Proficiency in cloud-native architectures (AWS/GCP/Azure) and containerization (Docker, Kubernetes) Experience with orchestration frameworks (Airflow, Ray, LangGraph, or similar) Familiarity with vector databases (Weaviate, Pinecone, FAISS), LLMOps platforms, and RAG design Architecture & Programming Solid experience in architectural patterns (microservices, event-driven, serverless) Proficient in Python and optionally Java/Go Knowledge of APIs (REST, GraphQL), streaming (Kafka), and observability tooling (Prometheus, ELK, Grafana) Tools & Platforms ML lifecycle tools: MLflow, Kubeflow, Vertex AI, Sagemaker, Hugging Face, etc. Prompt orchestration tools: LangChain, CrewAI, Semantic Kernel, DSPy (nice to have) Knowledge of security, privacy, and compliance (GDPR, SOC2, HIPAA, etc.) (ref:hirist.tech)