Solution Architect, AI/ML Engineering Consultant

Summary

Join ValGenesis, a leading digital validation platform provider, as an AI/ML Solution Architect. Lead the design and implementation of AI and machine learning features in our flagship products, focusing on knowledge management, semantic search, image processing, and predictive analytics. You will build scalable AI/ML models, implement image processing solutions, and define AI architecture. This role requires deep technical expertise, a strong grasp of regulated industry needs, and experience deploying scalable AI/ML systems. You will also collaborate with cross-functional teams and ensure compliance with regulatory requirements. The ideal candidate will have a strong background in AI/ML, data management, and life sciences validation processes.

Requirements

• Bachelor’s or Master’s in Computer Science, Data Science, or a related field
• 8+ years in AI/ML solution development
• Proven software development experience with life sciences or other regulated industries
• Strong analytical thinking and problem-solving skills
• Excellent communication and collaboration abilities
• Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face
• Libraries: Pandas, NumPy, SciPy, OpenCV (for image processing)
• Platforms: Microsoft Azure Machine Learning, AWS Sagemaker, Google AI Platform
• Techniques: NLP, deep learning, computer vision, time-series analysis, reinforcement learning
• Databases: MongoDB, PostgreSQL, Neo4j (graph databases)
• Big Data Tools: Apache Hadoop, Spark, Kafka for data pipelines
• Visualization: Power BI, Tableau, Matplotlib, Seaborn
• Containerization: Docker, Kubernetes
• CI/CD Tools: Jenkins, GitLab, CircleCI
• Version Control: Git, GitHub, Bitbuckets
• Programming Languages: Python, R, Java, and optionally Julia for advanced statistical analysis
• Cloud Infrastructure :Platforms: AWS, Azure, Google Cloud Platform
• Storage: S3, BigQuery, Azure Data Lake
• Security: IAM, VPC, Key Management Services for regulated environments
• Knowledge of life sciences validation processes and regulatory compliance (FDA 21 CFR Part 11, GxP) + Familiarity with CPV, APQR, and Statistical Process Control (SPC)

Responsibilities

• Build scalable AI/ML models for document classification, intelligent search, and predictive analytics
• Implement image processing solutions for visual inspections and anomaly detection in validation processes
• Define the AI architecture and select appropriate technologies from a pool of open-source and commercial offerings. Select cloud, on-premises or hybrid deployment models
• Ensure new tools are well-integrated with existing data management and analytics tools
• Deploy AI/ML solutions in cloud-based environments with high availability and security
• Stay current with the latest advancements in machine learning and artificial intelligence, and actively shape the application of AI/ML within the life science industry
• Provide mentorship to team of AI/ML engineers, fostering a collaborative environment conducive to ongoing research and development
• Architect AI-driven knowledge management systems for life sciences datasets
• Design efficient search tools using natural language processing (NLP) to enable rapid data retrieval
• Develop statistical models and machine learning pipelines for batch monitoring, failure prediction, and process optimization
• Work closely with cross-functional teams, including product managers, data scientists, validation specialists, to identify and pilot the use cases
• Discuss the feasibility of use cases along with architectural design with product functional teams and translate the product vision into realistic technical implementation
• Bring attention to misaligned initiatives and impractical use cases
• Ensure compliance with FDA, EMA and other global regulatory requirements
• Research emerging technologies and recommend the adoption of advanced AI/ML frameworks
• Guide the engineering team in implementing best practices for AI/ML development