Full-Time
Platform Product Manager
AI/ML
ValGenesis
501-1,000 employees
Cloud-based validation lifecycle management platform
No salary listed
Hyderabad, Telangana, India + 2 more
More locations: Chennai, Tamil Nadu, India | Bengaluru, Karnataka, India
In Person
Onsite in India; Chennai, Hyderabad, and Bangalore offices, 5 days/week.
Bachelor's, Master's, PhD
 Product (1) |
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- Bachelor’s or Master’s degree in Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative field.
- PhD strongly preferred in Statistics, Machine Learning, or a related discipline.
- Deep expertise in statistical methods, including: SPC (control charts), process capability analysis; Regression, ANOVA, DOE; Multivariate methods (PCA, PLS, MSPC); Time-series analysis.
- Strong working knowledge of machine learning techniques: Supervised learning (regression, classification); Unsupervised learning (clustering, anomaly detection); Forecasting and probabilistic modeling.
- Experience with generative AI and NLP, particularly for automated insights and content generation.
- Hands-on experience with tools such as: Python (pandas, scikit-learn, statsmodels); R, SAS, or equivalent statistical environments.
- Strong understanding of: Model validation, performance evaluation, and bias/variance tradeoffs; Explainability techniques (e.g., SHAP, LIME); MLOps concepts (model deployment, monitoring, retraining).
- Experience building or defining platform-level capabilities (APIs, shared services, reusable components).
- Familiarity with cloud platforms (AWS, Azure, GCP) and modern data architectures.
- Understanding of data engineering concepts, including pipelines, data quality, and feature engineering.
- Experience working in regulated industries (life sciences preferred but not required).
- Understanding of GxP expectations for software, including: 21 CFR Part 11, EU Annex 11; GAMP 5 / CSA principles for software validation; Familiarity with challenges of applying AI/ML in regulated environments (traceability, validation, auditability).
- 3+ years of product management experience in enterprise SaaS, data platforms, or AI/ML-driven products.
- Demonstrated ability to define highly technical product requirements for data science and engineering teams.
- Experience working in Agile environments with cross-functional teams.
- Strong analytical and strategic thinking with a platform mindset.
- Define and own the product strategy and roadmap for AI/ML and statistical capabilities as core platform services leveraged across multiple product domains (e.g., CPV, Process Management, Validation, Quality).
- Establish a unified AI/ML platform vision, including reusable models, services, and APIs that can be embedded across the ValGenesis product suite.
- Drive the evolution from fragmented statistical tooling to scalable, cloud-native, AI-powered platform capabilities.
- Identify and prioritize opportunities to apply machine learning, statistical modeling, and generative AI to improve decision-making, automation, and insights across the platform.
- Partner closely with AI/ML engineering and data platform teams to align on architecture, scalability, and long-term technical direction.
- Act as the subject matter expert (SME) for statistical methods, machine learning, and applied AI within the product organization.
- Define platform-level capabilities for: Statistical modeling frameworks (SPC, multivariate analysis, time-series analysis); Machine learning services (prediction, classification, anomaly detection); Generative AI services (automated insights, narrative generation, copilots).
- Establish standards for: Model selection, evaluation, and performance metrics; Feature engineering and data requirements; Model explainability and interpretability.
- Collaborate with data scientists and ML engineers to translate advanced analytical methods into scalable, reusable product features.
- Define requirements for model lifecycle management, including training, validation, monitoring, and retraining in regulated environments.
- Ensure platform capabilities support compliance with GxP expectations, including auditability, traceability, and validation of AI/ML models.
- Partner with engineering on: AI/ML platform architecture; Data pipelines and feature stores; Model deployment patterns (batch, real-time, hybrid); API design for AI/ML services.
- Collaborate with UX/UI to ensure complex statistical and AI outputs are translated into intuitive, actionable user experiences.
- Drive consistency and reuse of AI/ML capabilities across products through platform-first design principles.
- Serve as the central AI/ML expert bridging Product, Engineering, Data Science, and Go-To-Market teams.
- Engage with customers, data scientists, and technical stakeholders to validate platform capabilities and ensure real-world applicability.
- Support Sales, Customer Success, and Professional Services as the go-to expert on AI/ML and statistical functionality.
- Influence internal teams on best practices for adopting AI/ML capabilities across the product suite.
- Partner with Product Marketing to articulate the value of ValGenesis AI/ML platform capabilities versus point solutions and legacy statistical tools.
- Monitor industry trends in: Applied AI/ML in regulated industries; Statistical innovation and data science tooling; Regulatory perspectives on AI/ML in GxP environments.
- Contribute to thought leadership through whitepapers, webinars, and customer engagements.
- Prior experience in a platform product management role.
- Experience delivering AI/ML capabilities as part of a SaaS platform.
- Background in life sciences, pharma, or other regulated industries.
- Familiarity with MLOps frameworks and tools.
- Published work, speaking engagements, or recognized expertise in AI/ML or applied statistics
ValGenesis provides a cloud-based Validation Lifecycle Management System (VLMS) that digitizes the entire validation lifecycle from planning to archiving for life sciences, delivered as a SaaS and compliant with FDA 21 CFR Part 11 and EU Annex 11. The platform includes AI-enabled modules like iVal, iClean, and iRisk, and expanded after acquiring 4Tune Engineering to add risk management and continuous process verification, plus the 2025 Smart GxP AI-powered platform and VLMS Express for rapid deployment to smaller firms. It differentiates from competitors by offering a fully paperless, end-to-end validation lifecycle and a large installed base including 30 of the top 50 global life sciences companies. Its goal is to reduce validation costs and cycle times while preserving regulatory traceability and compliance across validated operations.
Company Size
501-1,000
Company Stage
Debt Financing
Total Funding
$40.4M
Headquarters
San Francisco, California
Founded
2005
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Simplify's Take
What believers are saying
- Ulrich Medical's June 2026 win validates ValGenesis against enterprise SAP modernization budgets.
- Westbourne expands delivery capacity without ValGenesis building a costly services army.
- ValGenesis's 2025 financing and 2026 Smart GxP push fund AI-native product expansion.
What critics are saying
- Validfor and Kneat attack ValGenesis with faster AI validation workflows in 2026.
- Ulrich Medical's SAP rollout exposes ValGenesis to implementation slippage and partner dependence.
- By 2027, commoditized AI validation destroys ValGenesis pricing power and margins.
What makes ValGenesis unique
- ValGenesis Smart GxP unifies validation and process lifecycle management across R&D and manufacturing.
- Ulrich Medical chose iVal on June 16, 2026, to replace manual CSV during SAP rollout.
- April 21, 2026 Westbourne partnership extends ValGenesis implementation and support across global customers.
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Benefits
Hybrid Work Options
Growth & Insights and Company News
6 month growth
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↑ 1%ValGenesis, the digital validation lifecycle management platform provider, has appointed Wayne Baker as chief revenue officer. Baker will oversee global sales strategy, customer expansion, and commercial execution across key markets. Baker brings over 25 years of experience in technology and life sciences. He previously served as chief commercial officer at Greenphire and chief sales officer at Advanced Health Media. The appointment comes as life sciences companies increasingly adopt AI-enabled validation processes. ValGenesis offers Smart GxP, an AI-native validation platform, and VAL, a governed AI system for executing validation work. Baker will focus on scaling global sales and helping customers adopt the company's platform across validation, process development, and manufacturing. ValGenesis serves life sciences companies worldwide, digitising commissioning, qualification, and validation processes.
Ulrich Medical Selects ValGenesis iVal(TM) for SAP-Driven CSV Upgrade. SANTA CLARA, Calif.-(BUSINESS WIRE)-ValGenesis Inc., the market leader in enterprise digital validation, announced that Ulrich Medical has selected ValGenesis iVal(TM) to modernize computer system validation (CSV) processes in support of its broader digital transformation and upcoming SAP implementation. Ulrich Medical has selected ValGenesis iVal(TM) to modernize computer system validation (CSV) processes in support of its broader digital transformation and upcoming SAP implementation. Share The Germany-based medical device company will replace manual validation processes with a digital approach to manage increased CSV activity associated with the SAP rollout. The initial deployment will begin at Ulrich Medical's headquarters, with plans for global expansion. Part of the AI-enabled ValGenesis Smart GxP(TM) platform, iVal centralizes validation planning, test authoring, and execution to enable more efficient and scalable CSV processes. With offline execution, automated deviation management, integrated risk assessments, and change impact analysis, the platform helps organizations streamline validation workflows, improve traceability, and maintain regulatory compliance across global operations. "Modernizing CSV was a prerequisite for our SAP rollout," said Matthias Novotny, Head of Process and Lean Management at Ulrich Medical. "ValGenesis gives us the efficiency we need to manage a significantly higher validation workload with greater accuracy and consistency, allowing us to keep pace with evolving global regulations without overstretching our team." "As medical device companies expand digital transformation initiatives and enterprise system deployments, they face growing pressure to manage validation activities more efficiently while maintaining compliance," said Anna Beamish, vice president of global sales at ValGenesis. "By implementing iVal, Ulrich Medical is moving toward a digital validation approach that can scale with its global operations and long-term growth." About Ulrich Medical Ulrich Medical develops, manufactures, and markets innovative medical technology. Founded in 1912, the company celebrates its 114th anniversary this year. Healthcare professionals worldwide rely on its decades of expertise. With product divisions in spinal implants and contrast media injectors for CT and MRI, Ulrich Medical offers a broad portfolio of advanced solutions. The company is among the few in the industry to retain both development and production in Germany, supported by state-of-the-art manufacturing technologies. As an owner-operated business, it remains independent and continues to deliver steady, sustainable growth. For more information, visit ulrichmedical.com About ValGenesis Inc. ValGenesis, Inc. is the global leader in enterprise digital validation. Serving the life sciences industry for nearly two decades, ValGenesis enables companies to digitize their commissioning, qualification, and validation processes through its AI-enabled ValGenesis Smart GxP(TM) platform, which includes solutions for risk management, cleaning validation, continued process verification, and CMC development. ValGenesis helps customers worldwide reduce costs, improve compliance, and accelerate innovation. For more information, visit valgenesis.com Contacts. Althea D'Sylva, ValGenesis Communications, +1 510-445-0505 Ex.1026 [email protected]
ValGenesis has launched the next generation of VAL (ValGenesis AI), bringing governed artificial intelligence to the validation lifecycle for life sciences companies. The platform will debut at INTERPHEX on 21-23 April in New York City, with a limited pilot programme for qualified firms. VAL operates within governed workflows in digital validation systems, using companies' approved validation documents, enterprise data, policies and regulatory guidance as guardrails. The system supports protocol generation, gap assessment, execution review and anomaly identification whilst maintaining human oversight and regulatory traceability. ValGenesis claims the AI-enabled platform can achieve up to 80% reduction in validation time and cost compared with manual processes, and deliver at least 50% greater efficiency than conventional digital validation. The company is the market leader in digital validation lifecycle management.
Validfor vs ValGenesis: which platform delivers better validation data visibility? Last updated: April 11, 2026 6:39 am In modern pharmaceutical validation environments, data visibility is no longer a secondary feature. It has become a strategic requirement. As validation activities expand across systems, sites, and lifecycle stages, organizations must ensure that validation data is accessible, actionable, and aligned with compliance objectives. Validation platforms are increasingly evaluated based on how effectively they enable decision-making through data transparency. Leaders want real-time insight into validation status, risks, bottlenecks, and performance trends. Two platforms frequently compared in this context are Validfor and ValGenesis. ValGenesis is widely known for structured lifecycle reporting and enterprise governance dashboards, while Validfor represents a newer generation of AI-driven validation platforms focused on dynamic data intelligence. This guide explores how each platform supports validation data visibility in modern pharma organizations. The strategic importance of validation data visibility. Validation programs generate large volumes of operational and compliance data. Without effective visibility mechanisms, organizations may face: * Delayed decision-making * Increased compliance risk * Operational inefficiencies * Difficulty prioritizing validation activities * Limited executive oversight Modern validation platforms must transform validation data into actionable insights rather than static documentation. Validfor vs ValGenesis at a glance. | Category | Validfor | ValGenesis | | Data visibility model | Real-time AI-driven validation intelligence | Structured lifecycle reporting dashboards | | Decision support | Dynamic workflow insights | Governance-oriented reporting frameworks | | Data accessibility | Operational-level real-time visibility | Enterprise-level structured transparency | | Best fit | Agile validation environments | Governance-driven global organizations | 1. Static reporting vs dynamic intelligence. ValGenesis provides strong lifecycle reporting capabilities. Its dashboards support enterprise governance by consolidating validation data into structured views suitable for audit readiness and executive oversight. This model emphasizes consistency and control, ensuring that validation status can be tracked systematically across sites. Validfor focuses on dynamic intelligence. Instead of presenting validation data primarily as structured reports, it aims to deliver real-time operational insights that support faster decision cycles. This reflects a key philosophical difference: * ValGenesis | visibility through governance reporting * Validfor | visibility through workflow intelligence 2. Real-time insight and operational responsiveness. In fast-moving validation environments, real-time visibility can significantly impact performance. ValGenesis provides comprehensive lifecycle tracking, but insight generation often aligns with structured reporting cycles. Validfor emphasizes continuous data accessibility. AI-driven insights aim to help validation teams respond to risks and bottlenecks as they emerge. This capability becomes increasingly important as validation volumes and complexity grow. 3. Enterprise oversight vs execution-level transparency. Different stakeholders require different levels of validation data visibility. ValGenesis excels at enterprise oversight. Its reporting model supports governance teams and leadership functions seeking consolidated visibility. Validfor focuses more on execution-level transparency. By providing operational teams with actionable insights, it aims to improve day-to-day validation performance. Organizations must determine which level of visibility is more strategically valuable. 4. Data-driven validation strategy alignment. As validation becomes increasingly data-driven, platforms must support predictive and risk-based decision-making. ValGenesis supports this through structured lifecycle analytics and historical trend analysis. Validfor positions AI-assisted intelligence as a core capability. By enabling dynamic prioritization and performance optimization, it aims to move validation from reactive reporting to proactive management. This distinction reflects the broader industry shift toward intelligent validation ecosystems. 5. Future direction of validation data visibility. The future of validation visibility lies in combining governance transparency with operational intelligence. ValGenesis provides a strong foundation for structured lifecycle governance. Validfor aligns more closely with emerging trends toward real-time validation intelligence and AI-supported decision-making. Organizations must consider not only current reporting needs but also future data strategy requirements. Which platform delivers better validation data visibility? Choose ValGenesis if: * You prioritize structured enterprise reporting * You require consolidated lifecycle governance dashboards * You value standardized validation oversight Choose Validfor if: * You want real-time validation insights * You aim to enable faster operational decisions * You prioritize AI-driven validation intelligence Final verdict. ValGenesis remains one of the strongest platforms for organizations seeking comprehensive lifecycle reporting and governance-driven validation visibility. However, as validation expectations evolve toward agility, intelligence, and proactive decision-making, platforms focused on real-time data utilization are gaining strategic relevance. Validfor's AI-driven workflow insights and dynamic visibility model make it particularly compelling for organizations seeking to transform validation data into operational advantage. Ultimately, the choice depends on whether validation visibility is defined primarily by governance reporting or by actionable intelligence. In recent years, validation processes across the pharmaceutical industry have been undergoing a major transformation. Workflows that were traditionally managed through paper documentation, spreadsheets and manual review cycles are increasingly moving toward digital validation platforms. As a result, life sciences organizations often evaluate solutions such as Kneat, Validfor, ValGenesis, MasterControl and Veeva when modernizing validation lifecycle management and compliance documentation. Originally posted 2025-12-25 22:11:37. News & research. Meta Description: Learn how CSV and VLM software enable audit-ready, AI-driven compliance in regulated life sciences through continuous traceability, automation,... April 10, 2026 Quality Management Systems (QMS) are essential for organizations in regulated industries such as pharmaceuticals, biotechnology, and medical devices. Choosing the... April 10, 2026 Audit management is a vital process in regulated industries such as pharmaceuticals, biotechnology, and medical devices. Organizations must plan, execute,... April 10, 2026 Validfor is rapidly emerging as a next-generation digital validation platform, designed to address the evolving needs of modern pharmaceutical and... April 10, 2026
ValGenesis announces first ValConnect Innovation Day 2025 in Princeton, NJ.