Senior Veeva Vault QMS Expert: Support & Training

TechDigital Group; Indianapolis (IN); On-site; USD 60,000 - 100,000; Full time

Job summary

An established industry player is seeking an experienced Veeva Vault QMS specialist with over 5 years of expertise in quality management processes. This dynamic role involves providing expert support, collaborating with cross-functional teams, and ensuring compliance with regulatory standards. You will manage and configure the Veeva Vault applications while conducting training sessions for users. If you have a passion for delivering exceptional support in a challenging environment and a solid background in Veeva Vault QMS, this opportunity is perfect for you. Join a forward-thinking team dedicated to excellence in the healthcare sector.

Qualifications

• 5+ years of experience with Veeva Vault QMS and quality management processes.
• Strong communication and collaboration skills are essential for this role.

Responsibilities

• Provide expert support for Veeva Vault QMS and manage configurations.
• Collaborate with teams to troubleshoot issues and ensure compliance.

Skills

Veeva Vault QMS

Communication Skills

Collaboration Skills

Regulatory Requirements Knowledge

Tools

Veeva Vault

ITIL

ITSM

Job description

Python Technical Lead - Data Analysis, SQL / Machine Learning Engineer (Generative AI & Cloud)

Responsibilities
Generative AI Development:
Design, develop, and fine-tune Generative AI solutions using models like Google's Gemini for tasks such as information extraction, document summarization, and report generation.
Architect and implement advanced Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and provide verifiable, context-aware responses.
Research and apply emerging GenAI techniques, such as agentic frameworks, to build more autonomous and capable systems.
End-to-End Machine Learning:
Design and deploy a wide range of ML models (classification, regression, forecasting, etc.) on Google Cloud Platform.
Build and maintain robust, automated MLOps pipelines for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI, BigQuery. etc.
Conduct deep data analysis to uncover insights, validate hypotheses, and guide feature engineering for improved model performance.
Collaboration & Strategy:
Partner closely with data scientists, software engineers, and other business stakeholders to frame problem statements, define technical requirements and deliver integrated AI/ML solutions.
Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of our machine learning systems.
Continuously evaluate and stay current with the latest advancements in the ML and GenAI landscape.

Qualifications
Experience: 5+ years of professional experience building and deploying machine learning models in a production environment.
Education: Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
Programming: Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit-learn, Pandas).
Data & SQL: Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
Generative AI: Demonstrable, hands-on experience in prompt engineering and/or fine-tuning Large Language Models (e.g., Gemini).
Cloud Platform: Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform (GCP).
MLOps: Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).

Qualifications:
Master's or PhD in a relevant field.
Specific experience with GCP services like Vertex AI, BigQuery, Google Cloud Storage, and GKE.
Experience building RAG systems from the ground up.
Proven ability to lead technical projects and mentor other engineers.