5 Generative Jobs

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) • Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. • Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) • Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning • Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models • Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. • Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) • Experience applying various machine learning techniques and understanding the key parameters that affect their performance • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs • Excellent verbal and written communication • Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: • Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: • Connect with internal / external POC to understand the business requirements • Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis • Create project plan and sprints for milestones / deliverables • Spin VM, create and optimize clusters for Data Science workflows • Create data pipelines to ingest data effectively • Assure the quality of data with proactive checks and resolve the gaps • Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms • Research whether similar solutions have been already developed before building ML models • Create optimized data models to query relevant data efficiently • Run relevant ML / DL algorithms for business goal seek • Optimize and validate these ML / DL models to scale • Create light applications, simulators, and scenario builders to help business consume the end outputs • Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively • Integrate and operationalize the models in client ecosystem • Document project artifacts and log failures and exceptions. • Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks

Design, develop, and deploy applications supporting pharmacovigilance systems Build and maintain E2E data reconciliation tools for adverse events and product complaints Develop AI-based solutions using Generative AI / LLMs (e.g., GPT) to drive decision-making and process efficiency Rapidly prototype new concepts into functional code Perform code reviews and ensure adherence to coding standards and best practices Create and maintain architecture, design, deployment, and disaster recovery documentation Identify and resolve technical challenges and production issues Collaborate with cross-functional teams to gather requirements and prioritize enhancements Ensure compliance with GxP validation and change control processes Drive automation and continuous improvement across drug-safety systems Provide root cause analysis and support for pharmacovigilance-related systems Ensure system architecture aligns with enterprise development standards Stay updated on emerging trends in software, AI, and safety platforms Functional Skills Must-Have Skills Proficiency in database programming and modeling using Oracle SQL and PostgreSQL Hands-on experience with Java or Python development Familiarity with reporting tools like Tableau, Cognos, Business Objects Working knowledge of AI/ML, NLP, NLG, and RPA technologies Experience with API integrations (MuleSoft) and ETL tools (Informatica, Databricks) Deep understanding of the Software Development Life Cycle (SDLC) Good-to-Have Skills Experience with COTS Pharmacovigilance Platforms (e.g., Argus Safety) Knowledge of GxP system management and validation SAFe Agile Software Engineer certification Soft Skills Excellent communication and collaboration skills Strong analytical and problem-solving mindset Ability to work in global, virtual teams with minimal supervision High self-motivation and accountability Adaptability in ambiguous environments and ability to prioritize tasks Leadership and peer-influencing abilities Basic Qualifications Master's degree with 46 years of experience in software development OR Bachelor's degree with 68 years of experience OR Diploma with 1012 years of experience

Role & responsibilities Generative AI architect Preferred candidate profile Perks and benefits

Role & responsibilities Generative AI architect Preferred candidate profile Perks and benefits

Role & responsibilities Generative AI architect Preferred candidate profile Perks and benefits