Job Summary
We are looking for a  Senior Associate Product Management to develop, implement, and sustain the digital strategy for R&D. 

Roles & Responsibilities

Key Responsibilities & Requirements

• Define product vision and strategy: Establish a clear roadmap for digital solutions in computational modeling and molecular dynamics.

• Manage end-to-end product lifecycle: Oversee ideation, design, development, launch, and post-market optimization of R&D digital tools.

• Collaborate with cross-functional teams: Work closely with scientists, data engineers, regulatory experts, and business stakeholders.

• Integrate advanced technologies: Drive adoption of machine learning, generative AI, and high-performance computing in pharma R&D.

• Ensure regulatory compliance: Align digital products with FDA, EMA, and ICH guidelines throughout the development process.

• Translate scientific needs into digital solutions:  Gen AI Agents, Prompt engineering sessions

• Monitor performance and outcomes: Use data-driven insights to measure product success and refine strategies.

• Champion innovation: Identify emerging digital trends and incorporate them into the pharma R&D ecosystem.

• Engage stakeholders: Communicate product vision, updates, and outcomes effectively to leadership and external partners.

• Drive user adoption and satisfaction: Ensure scientists and researchers find value in digital tools through training, support, and feedback loops.

We're looking for a detail-oriented and organized Accounts Assistant to join our finance team in Udaipur, India. In this role, you'll play a vital part in maintaining accurate financial records and supporting our accounting operations. You'll work collaboratively with the finance team to ensure smooth day-to-day accounting processes while demonstrating a commitment to accuracy, efficiency, and transparency. If you're analytical, proactive, and eager to grow your accounting career in a supportive environment, we'd love to hear from you!

• Process and manage accounts receivable (AR) and billing activities, including guest invoices, city ledger transfers, and follow-up on overdue accounts within established timelines
• Review, code, and input vendor invoices accurately; reconcile supplier statements and maintain organized accounts payable (AP) records
• Reconcile daily revenue streams, including cash drops, credit card receipts, and Property Management System (PMS) adjustments to ensure accuracy and identify discrepancies
• Assist with month-end financial closing activities, including bank reconciliations, accruals, and preparation of financial reports under the guidance of the Financial Controller
• Maintain accurate general ledger records and ensure compliance with tax regulations, including GST/VAT requirements
• Support inventory tracking and financial record-keeping to ensure data integrity across all accounting systems
• Collaborate with cross-functional teams to resolve accounting issues and provide timely, accurate financial information
• Perform data entry and reconciliation tasks with meticulous attention to detail and numerical accuracy
• Contribute to continuous process improvements by identifying inefficiencies and suggesting solutions to enhance operational effectiveness

Job Description

We are seeking an experienced AI/ML Engineer (5–8 years) with strong hands-on expertise in end-to-end machine learning, GenAI solution development, data engineering, and cloud-native deployment. The role involves building scalable AI systems, designing LLM-based applications, and integrating enterprise-grade MLOps pipelines across any one of Azure, GCP, and AWS environments.

Key Responsibilities

• Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks.

• Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.

• Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.

• Work with cross-functional teams to translate business needs into AI-driven outcomes.

• Deploy workloads using Azure App Service, Cloud Run, Azure Bot Service, Dialogflow, and other cloud-native platforms.

• Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.

• Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools.

• Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot.

• Ensure scalable, secure, and cost-optimized deployment across Azure/GCP/AWS environments.