We are looking for a forward-thinking Data Scientist with expertise in Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering, and Knowledge Graph construction. You will be instrumental in designing intelligent NLP pipelines involving Named Entity Recognition (NER), Relationship Extraction, and semantic knowledge representation. The ideal candidate will also have practical experience in deploying Python-based APIs for model and service integration. This is a hands-on, cross-functional role where you’ll work at the intersection of cutting-edge AI models and domain-driven knowledge extraction. Key Responsibilities: Develop and fine-tune LLM-powered NLP pipelines for tasks such as NER, coreference resolution, entity linking, and relationship extraction. Design and build Knowledge Graphs by structuring information from unstructured or semi-structured text. Apply Prompt Engineering techniques to improve LLM performance in few-shot, zero-shot, and fine-tuned scenarios. Evaluate and optimize LLMs (e.g., OpenAI GPT, Claude, LLaMA, Mistral, or Falcon) for custom domain-specific NLP tasks. Build and deploy Python APIs (using Flask/Fast API) to serve ML/NLP models and access data from graph database. Collaborate with teams to translate business problems into structured use cases for model development. Understanding custom ontologies and entity schemas for corresponding domain. Work with graph databases like Neo4j or similar DBs and query using Cypher or SPARQL. Evaluate and track performance using both standard metrics and graph-based KPIs. Required Skills & Qualifications: Strong programming experience in Python and libraries such as PyTorch, TensorFlow, spaCy, scikit-learn, Hugging Face Transformers, LangChain, and OpenAI APIs. Deep understanding of NER, relationship extraction, co-reference resolution, and semantic parsing. Practical experience in working with or integrating LLMs for NLP applications, including prompt engineering and prompt tuning. Hands-on experience with graph database design and knowledge graph generation. Proficient in Python API development (Flask/FastAPI) for serving models and utilities. Strong background in data preprocessing, text normalization, and annotation frameworks. Understanding of LLM orchestration with tools like LangChain or workflow automation. Familiarity with version control, ML lifecycle tools (e.g., MLflow), and containerization (Docker). Nice to Have: Experience using LLMs for Information Extraction, summarization, or question answering over knowledge bases. Exposure to Graph Embeddings, GNNs, or semantic web technologies (RDF, OWL). Experience with cloud-based model deployment (AWS/GCP/Azure). Understanding of retrieval-augmented generation (RAG) pipelines and vector databases (e.g., Chroma, FAISS, Pinecone). Job Type: Full-time Pay: ₹1,200,000.00 - ₹2,400,000.00 per year Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Preferred) Experience: Natural Language Processing (NLP): 3 years (Preferred) Language: English & Tamil (Preferred) Location: Chennai, Tamil Nadu (Preferred) Work Location: In person
We are looking for a forward-thinking Data Scientist with expertise in Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering, and Knowledge Graph construction. You will be instrumental in designing intelligent NLP pipelines involving Named Entity Recognition (NER), Relationship Extraction, and semantic knowledge representation. The ideal candidate will also have practical experience in deploying Python-based APIs for model and service integration. This is a hands-on, cross-functional role where you’ll work at the intersection of cutting-edge AI models and domain-driven knowledge extraction. Key Responsibilities: Develop and fine-tune LLM-powered NLP pipelines for tasks such as NER, coreference resolution, entity linking, and relationship extraction. Design and build Knowledge Graphs by structuring information from unstructured or semi-structured text. Apply Prompt Engineering techniques to improve LLM performance in few-shot, zero-shot, and fine-tuned scenarios. Evaluate and optimize LLMs (e.g., OpenAI GPT, Claude, LLaMA, Mistral, or Falcon) for custom domain-specific NLP tasks. Build and deploy Python APIs (using Flask/Fast API) to serve ML/NLP models and access data from graph database. Collaborate with teams to translate business problems into structured use cases for model development. Understanding custom ontologies and entity schemas for corresponding domain. Work with graph databases like Neo4j or similar DBs and query using Cypher or SPARQL. Evaluate and track performance using both standard metrics and graph-based KPIs. Required Skills & Qualifications: Strong programming experience in Python and libraries such as PyTorch, TensorFlow, spaCy, scikit-learn, Hugging Face Transformers, LangChain, and OpenAI APIs. Deep understanding of NER, relationship extraction, co-reference resolution, and semantic parsing. Practical experience in working with or integrating LLMs for NLP applications, including prompt engineering and prompt tuning. Hands-on experience with graph database design and knowledge graph generation. Proficient in Python API development (Flask/FastAPI) for serving models and utilities. Strong background in data preprocessing, text normalization, and annotation frameworks. Understanding of LLM orchestration with tools like LangChain or workflow automation. Familiarity with version control, ML lifecycle tools (e.g., MLflow), and containerization (Docker). Nice to Have: Experience using LLMs for Information Extraction, summarization, or question answering over knowledge bases. Exposure to Graph Embeddings, GNNs, or semantic web technologies (RDF, OWL). Experience with cloud-based model deployment (AWS/GCP/Azure). Understanding of retrieval-augmented generation (RAG) pipelines and vector databases (e.g., Chroma, FAISS, Pinecone). Job Type: Full-time Pay: ₹1,200,000.00 - ₹2,400,000.00 per year Ability to commute/relocate: Selaiyur, Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Preferred) Experience: Natural Language Processing (NLP): 3 years (Preferred) Language: English & Tamil (Preferred) Location: Selaiyur, Chennai, Tamil Nadu (Preferred) Work Location: In person
We are looking for a forward-thinking Data Scientist with expertise in Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering, and Knowledge Graph construction. You will be instrumental in designing intelligent NLP pipelines involving Named Entity Recognition (NER), Relationship Extraction, and semantic knowledge representation. The ideal candidate will also have practical experience in deploying Python-based APIs for model and service integration. This is a hands-on, cross-functional role where you’ll work at the intersection of cutting-edge AI models and domain-driven knowledge extraction. Key Responsibilities: Develop and fine-tune LLM-powered NLP pipelines for tasks such as NER, coreference resolution, entity linking, and relationship extraction. Design and build Knowledge Graphs by structuring information from unstructured or semi-structured text. Apply Prompt Engineering techniques to improve LLM performance in few-shot, zero-shot, and fine-tuned scenarios. Evaluate and optimize LLMs (e.g., OpenAI GPT, Claude, LLaMA, Mistral, or Falcon) for custom domain-specific NLP tasks. Build and deploy Python APIs (using Flask/Fast API) to serve ML/NLP models and access data from graph database. Collaborate with teams to translate business problems into structured use cases for model development. Understanding custom ontologies and entity schemas for corresponding domain. Work with graph databases like Neo4j or similar DBs and query using Cypher or SPARQL. Evaluate and track performance using both standard metrics and graph-based KPIs. Required Skills & Qualifications: Strong programming experience in Python and libraries such as PyTorch, TensorFlow, spaCy, scikit-learn, Hugging Face Transformers, LangChain, and OpenAI APIs. Deep understanding of NER, relationship extraction, co-reference resolution, and semantic parsing. Practical experience in working with or integrating LLMs for NLP applications, including prompt engineering and prompt tuning. Hands-on experience with graph database design and knowledge graph generation. Proficient in Python API development (Flask/FastAPI) for serving models and utilities. Strong background in data preprocessing, text normalization, and annotation frameworks. Understanding of LLM orchestration with tools like LangChain or workflow automation. Familiarity with version control, ML lifecycle tools (e.g., MLflow), and containerization (Docker). Nice to Have: Experience using LLMs for Information Extraction, summarization, or question answering over knowledge bases. Exposure to Graph Embeddings, GNNs, or semantic web technologies (RDF, OWL). Experience with cloud-based model deployment (AWS/GCP/Azure). Understanding of retrieval-augmented generation (RAG) pipelines and vector databases (e.g., Chroma, FAISS, Pinecone). Job Type: Full-time Pay: ₹1,200,000.00 - ₹2,400,000.00 per year Ability to commute/relocate: Selaiyur, Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Preferred) Experience: Natural Language Processing (NLP): 3 years (Preferred) Language: English & Tamil (Preferred) Location: Selaiyur, Chennai, Tamil Nadu (Preferred) Work Location: In person
We are seeking a dedicated and technically sound Desktop Support Engineer to join our IT team in Chennai. The ideal candidate will have 2–3 years of hands-on experience , preferably within a healthcare or PV/CRO environment , providing user support, maintaining GDPs-compliant systems, and ensuring IT infrastructure supports regulated clinical and pharmacovigilance operations. Key Responsibilities Provide Level 1 & Level 2 support for desktops, laptops, printers, and mobile devices. Install, configure, and troubleshoot Windows OS, MS Office 365, and specialized tools used in PV/CRO (e.g., Argus Safety, Track Wise, clinical databases). Ensure compliance with GDPs , 21 CFR Part 11 , and HIPAA standards during support activities. Support user onboarding/offboarding, access rights, and hardware setup. Maintain detailed documentation of incidents, resolutions, SOPs, and system changes. Collaborate with IT infrastructure, validation, QA, and business teams on IT initiatives. Assist during system audits and support CAPA-related IT actions. Maintain IT asset inventory, conduct system health checks, and schedule routine maintenance. Required Skills & Qualifications Bachelor's degree in Computer Science , Information Technology , or related field. 2 to 3 years of relevant experience in desktop support or IT helpdesk roles. Experience supporting users in healthcare, pharma, or clinical research domains. Strong troubleshooting knowledge of Windows OS , Office 365 , Active Directory , VPN, and remote access tools. Familiarity with ticketing systems (e.g., Jira, ServiceNow). Understanding of GDPs systems, IT compliance , and audit documentation . Preferred Qualifications Certifications like CompTIA A+ , MCSA , or ITIL Foundation . Exposure to Argus Safety , Track Wise , or clinical EDC platforms . Experience working under IT SOPs in a regulated environment. Knowledge of basic networking and endpoint protection tools. What We Offer Competitive salary & performance-based bonuses Opportunity to grow within the clinical research / healthcare IT space Collaborative and compliance-focused work environment Exposure to global clients and regulated IT systems Job Type: Full-time Pay: ₹250,000.00 - ₹300,000.00 per year Work Location: In person
We are looking for a forward-thinking Data Scientist with expertise in Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering, and Knowledge Graph construction. You will be instrumental in designing intelligent NLP pipelines involving Named Entity Recognition (NER), Relationship Extraction, and semantic knowledge representation. The ideal candidate will also have practical experience in deploying Python-based APIs for model and service integration. This is a hands-on, cross-functional role where you’ll work at the intersection of cutting-edge AI models and domain-driven knowledge extraction. Key Responsibilities: Develop and fine-tune LLM-powered NLP pipelines for tasks such as NER, coreference resolution, entity linking, and relationship extraction. Design and build Knowledge Graphs by structuring information from unstructured or semi-structured text. Apply Prompt Engineering techniques to improve LLM performance in few-shot, zero-shot, and fine-tuned scenarios. Evaluate and optimize LLMs (e.g., OpenAI GPT, Claude, LLaMA, Mistral, or Falcon) for custom domain-specific NLP tasks. Build and deploy Python APIs (using Flask/Fast API) to serve ML/NLP models and access data from graph database. Collaborate with teams to translate business problems into structured use cases for model development. Understanding custom ontologies and entity schemas for corresponding domain. Work with graph databases like Neo4j or similar DBs and query using Cypher or SPARQL. Evaluate and track performance using both standard metrics and graph-based KPIs. Required Skills & Qualifications: Strong programming experience in Python and libraries such as PyTorch, TensorFlow, spaCy, scikit-learn, Hugging Face Transformers, LangChain, and OpenAI APIs. Deep understanding of NER, relationship extraction, co-reference resolution, and semantic parsing. Practical experience in working with or integrating LLMs for NLP applications, including prompt engineering and prompt tuning. Hands-on experience with graph database design and knowledge graph generation. Proficient in Python API development (Flask/FastAPI) for serving models and utilities. Strong background in data preprocessing, text normalization, and annotation frameworks. Understanding of LLM orchestration with tools like LangChain or workflow automation. Familiarity with version control, ML lifecycle tools (e.g., MLflow), and containerization (Docker). Nice to Have: Experience using LLMs for Information Extraction, summarization, or question answering over knowledge bases. Exposure to Graph Embeddings, GNNs, or semantic web technologies (RDF, OWL). Experience with cloud-based model deployment (AWS/GCP/Azure). Understanding of retrieval-augmented generation (RAG) pipelines and vector databases (e.g., Chroma, FAISS, Pinecone). Job Type: Full-time Pay: ₹1,200,000.00 - ₹2,400,000.00 per year Ability to commute/relocate: Selaiyur, Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Preferred) Experience: Natural Language Processing (NLP): 3 years (Preferred) Language: English & Tamil (Preferred) Location: Selaiyur, Chennai, Tamil Nadu (Preferred) Work Location: In person
Full Stack Software Developer -Pharmacovigilance / Safety Systems About the Role We are looking for a Full Stack Software Developer with strong experience in MERN stack (React.js, Node.js, Express.js, MongoDB, PostgreSQL) and hands-on exposure to pharmacovigilance / safety databases. This role offers the opportunity to design and enhance safety systems that enable global adverse event reporting, regulatory submissions, and medical dictionary integration. You will contribute to the development of validated, compliant applications critical to life sciences and healthcare. Key Responsibilities · Design, develop, and maintain full-stack applications using React.js, Node.js, Express.js, MongoDB, PostgreSQL. · Build scalable APIs and user interfaces for pharmacovigilance workflows. · Implement E2B R2 / R3 compliant case exchange and regulatory gateway submissions. · Integrate and manage medical dictionaries (MedDRA, WHO-DD). · Ensure compliance with ICH guidelines, 21 CFR Part 11, and validation standards. · Collaborate with pharmacovigilance SMEs, QA, and cross-functional teams. · Troubleshoot issues, optimize performance, and support validation activities. Required Skills & Experience · 4 - 5 years of hands-on full stack development in production environments. · Strong expertise in React.js, Node.js, Express.js, MongoDB, PostgreSQL. · Experience working with pharmacovigilance safety systems (e.g., Oracle Argus, ArisGlobal LifeSphere/ARISg, Veeva Vault Safety, SafetyEasy, Flex, or similar application). · Knowledge of MedDRA, WHO-DD, and integration workflows. · Understanding of E2B R2/R3 standards, ICH guidelines, gateway submissions, and 21 CFR Part 11 compliance. · Excellent problem-solving, coding, and debugging skills. · Strong communication skills and ability to work in cross-functional teams. Preferred / Nice-to-Have · Cloud experience (AWS, Azure). · Exposure to microservices, containerization (Docker/Kubernetes). · Knowledge of regulatory reporting of safety reports (i.e.ICSR, DSUR, PBRER). What We Offer · Competitive salary package: ₹6 LPA - ₹15 LPA. · Opportunity to build mission-critical safety software in the life sciences domain. · Collaborative, office-based work culture in Chennai. · Professional growth and learning opportunities in regulated software development. Job Type: Full-time Pay: ₹600,000.00 - ₹1,500,000.00 per year Application Question(s): Experience with Azure App Services, Virtual Machines, Storage, Networking, and DevOps pipelines is a plus. Curren LPA: Expected LPA: Notice Period: Dob: Email ID: Need at least one reference name and contact details from the same organization where you are working currently: Education: Bachelor's (Preferred) Experience: Hands on full stack development in production environments: 4 years (Preferred) Location: Selaiyur, Chennai, Tamil Nadu (Preferred) Work Location: In person