Safety & PV AI and Machine Learning Specialist – Hyderabad (Hybrid)
Location: Hyderabad, India (Hybrid)
Job Type: Full-Time
Job ID: 25103964
About Syneos Health
Syneos Health® is a leading fully integrated biopharmaceutical solutions organization, delivering innovative solutions in clinical development, medical affairs, and commercial operations worldwide. With a presence in 110 countries and over 29,000 employees, we combine scientific expertise, advanced technology, and operational excellence to accelerate patient safety and regulatory compliance.
Our mission is to simplify and streamline clinical operations, ensuring both our clients and employees experience efficiency, collaboration, and growth.
Position Overview
The Safety & PV AI and Machine Learning Specialist will play a key technical and strategic role in Syneos Health’s Safety & Pharmacovigilance (PV) AI enablement initiatives. This position focuses on designing, developing, and implementing AI, machine learning (ML), and automation solutions to enhance pharmacovigilance workflows, improve operational efficiency, and maintain compliance with global regulatory standards.
This role is ideal for professionals with a blend of pharmacovigilance or life sciences expertise and hands-on AI/ML development experience, capable of building proof-of-concept AI applications, optimizing prompts, and deploying AI responsibly in a regulated environment.
Key Responsibilities
AI Solution Design & Development
Design, build, and test AI/ML prototypes and proof-of-concept solutions for PV workflows, including case intake, triage, data extraction, signal detection, and narrative generation.
Develop and optimize prompt engineering strategies for LLMs to support PV automation and decision-making.
Collaborate with Safety Tech, IT, and PV Operations to convert operational challenges into AI opportunities.
Technical Implementation & Integration
Evaluate and integrate AI technologies and APIs (NLP, generative AI, computer vision, process automation) into PV systems and workflows.
Collaborate with developers and data engineers to ensure scalable, compliant AI deployments.
Data & Model Governance
Support model evaluation, validation, and monitoring to ensure accuracy, reliability, and regulatory compliance.
Contribute to AI governance frameworks, including documentation, explainability, and risk management per GxP, GDPR, and 21 CFR Part 11 standards.
Collaboration & Knowledge Sharing
Work cross-functionally with Safety Operations, Data Science, IT, and Business Analysts to align AI initiatives with PV business needs.
Provide expertise on AI trends, tools, and best practices relevant to pharmacovigilance and life sciences.
Required Qualifications
Bachelor’s or Master’s degree in Life Sciences, Data Science, Computer Science, Engineering, or related field. Advanced degree preferred.
3–5+ years of experience in pharmacovigilance, drug safety, life sciences operations, or AI/ML development within a regulated environment.
Hands-on experience with AI/ML model development (Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI API).
Expertise in NLP, Large Language Models (LLMs), prompt engineering, and AI pilot applications.
Knowledge of GxP, 21 CFR Part 11, data privacy, and global AI regulations.
Preferred Skills
Familiarity with pharmacovigilance databases, case processing systems, and PV workflows.
Experience with automation and RPA tools.
Strong analytical, communication, and documentation skills.
Ability to translate complex technical AI concepts to non-technical stakeholders.
Passion for innovation, AI adoption, and continuous improvement.
Location & Work Environment
Hybrid work model in Hyderabad, India.
Collaboration with global teams across multiple time zones.
Why Join Syneos Health?
Lead cutting-edge AI initiatives in pharmacovigilance.
Drive automation, innovation, and patient safety outcomes globally.
Work in a collaborative, diverse, and growth-focused environment.
Shape the future of AI-enabled drug safety operations.
Apply now to join Syneos Health as a Safety & PV AI and Machine Learning Specialist and contribute to the future of pharmacovigilance innovation.
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