Location: USA (Remote/Hybrid), India (Chennai, Hyderabad, Bengaluru)

Department: Engineering

Type: Contract, Part-Time, Full-Time

About ValGenesis

ValGenesis is a leading digital validation platform provider for life sciences companies. ValGenesis suite of products are used by 30 of the top 50 global pharmaceutical and biotech companies to achieve digital transformation, total compliance and manufacturing excellence/intelligence across their product lifecycle.

Learn more about working for ValGenesis, the de facto standard for paperless validation in Life Sciences: https://www.youtube.com/watch?v=tASq7Ld0JsQ

Job Description:

We are seeking a highly skilled AI/ML Solution Architect to lead the design and implementation of advanced AI and machine learning backed features in our flag ship products. This role focuses on knowledge management, semantic search, image processing, and predictive analytics to support Continued Process Verification (CPV) and Annual Product Quality Review (APQR) programs. The ideal candidate will have deep technical expertise, a strong grasp of regulated industry needs, and experience in deploying scalable AI/ML systems.

AI/ML Development & Implementation

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.

Data Management & Knowledge Systems

Architect AI-driven knowledge management systems for life sciences datasets.

Design efficient search tools using natural language processing (NLP) to enable rapid data retrieval.

CPV & APQR Automation

Develop statistical models and machine learning pipelines for batch monitoring, failure prediction, and process optimization.

Collaboration & Compliance

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.

Innovation & Strategy

Research emerging technologies and recommend the adoption of advanced AI/ML frameworks.
Guide the engineering team in implementing best practices for AI/ML development.

Skills and Tools Required:

Machine Learning & AI Tools

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.

Big Data & Analytics

Databases: MongoDB, PostgreSQL, Neo4j (graph databases).
Big Data Tools: Apache Hadoop, Spark, Kafka for data pipelines.
Visualization: Power BI, Tableau, Matplotlib, Seaborn.

DevOps & Deployment

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.

Domain-Specific Knowledge: Knowledge of life sciences validation processes and regulatory compliance (FDA 21 CFR Part 11, GxP) + Familiarity with CPV, APQR, and Statistical Process Control (SPC).

Qualifications:

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.

ValGenesis is an Equal Opportunity Employer. All qualified applicants will be considered for employment without regard to race, age, national origin, religion, marital status, sexual orientation, ancestry, color, gender identity / expression, family / medical care leave, genetic information, medical condition, physical / mental disability, political affiliation, status as a protected veteran, status as a person with a disability, or other characteristics protected by laws or regulations.

ValGenesis

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