Valgenesis1mo ago

Engineering Manager / Architect — Data Science & ML

Chennai,ChennaiFull-Timemid

EngineeringManagementEngineering Manager

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Quick Summary

Overview

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…

Requirements Summary

Experience at a life sciences SaaS company or pharmaceutical analytics vendor Contributions to open-source ML libraries, statistical packages, or pharmaceutical data standards (CDISC, SDTM, ADaM).

Technical Tools

awsazuregcpapi-designcode-reviewdeep-learningmachine-learningperformance-managementsaasstatistical-modeling

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.valgenesis.com/about

About the Role:

Perform statistical analysis and apply advanced statistical modeling techniques

Design, train, and optimize machine learning and deep learning models for various business use cases

Deploy models into production environments and ensure reliable model serving and scalability

Build and maintain robust GxP-compliant ML pipelines on cloud infrastructure (AWS/Azure/GCP) including data ingestion, preprocessing, training, and monitoring

Evaluate model performance using appropriate metrics and continuously improve accuracy and efficiency

Collaborate with cross-functional teams (engineering, product, and business stakeholders) to translate requirements into data-driven solutions

Monitor deployed models for performance drift and retrain models as necessary

Ensure best practices in model versioning, reproducibility, and documentation

Conduct hands-on code reviews, architectural reviews, and model performance evaluations for all team deliverables.

Directly manage and mentor a team of 4–8 ML engineers, data scientists, and data engineers with defined technical goals and OKRs.

Set individual development plans, run performance reviews, and build a culture of technical excellence, scientific rigor, and continuous learning.

Recruit, interview, and hire top data science and ML engineering talent with strong domain experience in life sciences or regulated industries.

Foster a collaborative environment where the team is empowered to propose, prototype, and ship novel ML solutions with speed and quality.

Act as the technical escalation point for the team — unblocking architecture decisions, performance issues, and regulatory compliance questions.

Partner with the Product Manager (Data Science) to translate business and regulatory requirements into precise, implementable ML specifications.

Collaborate with platform engineering on data infrastructure, API design, and integration of ML models into the ValGenesis SaaS platform.

Work with the Quality and Compliance team to ensure all ML features are properly validated, documented, and audit-trail compliant under 21 CFR Part 11.

Engage with strategic customers and key opinion leaders (KOLs) in the pharma industry to validate model approaches and gather technical feedback.

Present technical architecture and model performance to executive leadership, customer CTOs, and regulatory affairs teams.

Establish MLOps practices: model versioning, experiment tracking, automated retraining triggers, drift detection, and production monitoring.

Define model governance standards for the GxP environment, including model qualification, change control, and periodic review procedures.

Own the technical roadmap for the data science platform, balancing research innovation with production stability and regulatory compliance.

Degree in Statistics, Machine Learning, Computer Science, Biostatistics, Chemical Engineering, Pharmaceutical Sciences, or related quantitative field.

Bachelor’s degree considered only with 8+ years of directly relevant hands-on experience.

5+ years of hands-on data science and ML engineering experience, with at least 3 years in a technical leadership or architect role.

Proven track record of building and shipping production ML models at scale, not just research prototypes or POCs.

5+ years of experience in the pharmaceutical, biotech, or medical device industry in a technical role involving process data, quality analytics, or statistical modeling.

Demonstrated hands-on experience building all model types listed in the Technical Skills Matrix above.

Experience leading a team of 3+ data scientists or ML engineers with measurable outcomes.

PREFERRED QUALIFICATIONS

Experience at a life sciences SaaS company or pharmaceutical analytics vendor

Contributions to open-source ML libraries, statistical packages, or pharmaceutical data standards (CDISC, SDTM, ADaM).

Certified in cloud ML platforms (AWS ML Specialty, Azure Data Scientist, GCP ML Engineer).

Six Sigma Black Belt or ASQ CQE with a strong statistical application background.

Location & Eligibility

Where is the job

Chennai

On-site at the office

Who can apply

Same as job location

Listed under

Worldwide

Listing Details

Posted: April 1, 2026
First seen: April 1, 2026
Last seen: May 16, 2026

Posting Health

Days active: 45
Repost count: 0
Trust Level: 31%
Scored at: May 17, 2026

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Valgenesis

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ValGenesis Inc. is a leading provider of enterprise validation lifecycle management solutions (VLMS) for the life sciences industry, offering a digital transformation platform to manage compliance-based validation activities.

Employees

750

Founded

2005

Domain

Jobs

External application · ~5 min on Valgenesis's site

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