Job Overview
| Particulars | Details |
|---|---|
| Position | Model Building & Deep Learning Expert | AI/ML & Life Sciences |
| Company | Axtria |
| Location | Multiple Locations (As per Business Requirement) |
| Job Type | Full-Time |
| Experience | 4 - 12 years |
| Category / Department | IT |
| Application Mode |
🏢 About Axtria
Axtria is a global leader in AI-powered analytics, data management, and commercial solutions for the Life Sciences industry. Founded in 2010, Axtria helps pharmaceutical, biotechnology, and healthcare organizations transform complex data into actionable business intelligence and strategic decision-making capabilities.
By combining Artificial Intelligence, Advanced Analytics, Data Engineering, and Commercial Excellence, Axtria enables life sciences organizations to optimize patient engagement, accelerate drug commercialization, improve sales effectiveness, and deliver measurable business outcomes.
Today, Axtria serves leading global Life Sciences organizations with innovative AI-led solutions spanning the commercial-to-clinical spectrum.
Axtria helps organizations transform fragmented data into actionable intelligence through:
• Information Management
• Data Engineering
• Master Data Management
• Business Intelligence & Visualization
• Advanced Analytics
• Commercial Strategy
• AI-Powered Decision Intelligence
• Personalized Patient Engagement
• Sales and Marketing Optimization
🌟 Company Highlights
• Global Leader in Life Sciences Analytics
• AI-Powered Commercial Intelligence Solutions
• Enterprise Data & Analytics Platform Provider
• Advanced Analytics & Machine Learning Expertise
• Focus on Agentic AI and Future-Ready Technologies
• Global Presence Across Commercial and Clinical Domains
🎯 Vision
To be the leading data analytics partner transforming the Life Sciences industry.
🎯 Mission
To leverage Data and Artificial Intelligence for advancing groundbreaking treatments and improving lives globally.
💡 Core Values
Doing the R.I.G.H.T thing always.
💡 Editor's Note / Preparation Tip
For AI/ML roles at Axtria, recruiters and hiring managers primarily focus on practical machine learning implementation experience, mathematical understanding, and production deployment expertise rather than only academic knowledge.
✅ Resume Preparation Checklist
• Highlight end-to-end machine learning projects.
• Mention predictive modeling use cases and business impact.
• Include deep learning projects using TensorFlow or PyTorch.
• Showcase production deployment experience.
• Add healthcare, pharma, or life sciences experience if available.
• Include GitHub repositories, research publications, or technical blogs.
• Quantify achievements using metrics wherever possible.
• Mention cloud platforms and MLOps experience.
🎯 Interview Preparation Topics
Machine Learning
• Supervised Learning
• Unsupervised Learning
• Feature Engineering
• Model Evaluation
• Bias-Variance Tradeoff
• Ensemble Learning
Deep Learning
• ANN Architecture
• CNN Architecture
• Backpropagation
• Optimization Algorithms
• Transfer Learning
• Hyperparameter Tuning
Programming
• Python
• PySpark
• NumPy
• Pandas
• Data Processing
Frameworks
• TensorFlow
• PyTorch
Advanced Topics
• MLOps
• Model Deployment
• Distributed Training
• Real-Time Inference
• Model Monitoring
• Explainable AI
Life Sciences
• Healthcare Analytics
• Clinical Data
• Commercial Analytics
• Pharma Forecasting
💡 Frequently Asked Interview Questions
• Explain the difference between ANN and CNN.
• How do you handle overfitting in deep learning?
• Describe your most complex machine learning project.
• Explain backpropagation in neural networks.
• How do you optimize model performance?
• Explain the bias-variance tradeoff.
• What evaluation metrics do you use and why?
• How would you build a production ML pipeline?
• Explain feature engineering techniques.
• Describe your experience with PySpark.
• How do you deploy machine learning models in production?
• Explain a healthcare or life sciences use case you've worked on.
📌 Application Tips
• Highlight measurable business impact.
• Include model accuracy improvements and performance metrics.
• Mention production deployment experience prominently.
• Include research papers or open-source contributions if applicable.
• Ensure your resume is ATS-friendly.
• Apply only if you can join within the preferred timeline.
🚀 Pro Tip
Candidates who can explain the complete lifecycle of an AI solution—from business problem understanding, data engineering, feature selection, model building, hyperparameter tuning, deployment, monitoring, and business impact measurement—typically perform exceptionally well in senior AI interviews.
📝 Job Description
🚀 Axtria Hiring | Model Building & Deep Learning Expert | AI/ML & Life Sciences | Immediate Joiners Preferred
🏢 Company: Axtria – Ingenious Insights
💼 Position: Model Building & Deep Learning Expert
📌 Department: Artificial Intelligence / Machine Learning / Advanced Analytics
📍 Location: Multiple Locations (As per Business Requirement)
🧑💻 Experience: 4–12 Years
🏥 Domain Preference: Pharma / Life Sciences
⚡ Joining Preference: Immediate Joiners Preferred
🎓 Qualification: B.E. / B.Tech / M.Tech / MCA / M.Sc / PhD in Computer Science, AI, Data Science, Statistics, Biotechnology, or related fields
⏳ Employment Type: Full-Time
📧 Application Mode: Email Application
💼 Job Details
Position: Model Building & Deep Learning Expert
Experience: 4–12 Years
Domain: Pharma / Life Sciences (Preferred)
Employment Type: Full-Time
Joining Preference: Immediate Joiners
⭐ Preferred Skills
• TensorFlow
• PyTorch
• MLOps
• Real-Time Machine Learning Systems
• Data Engineering
• Cloud Platforms
• Healthcare Analytics
• Life Sciences Domain Knowledge
• Generative AI Fundamentals
• Agentic AI Concepts
🛠 Tech Stack
Programming Languages
• Python
• PySpark
Machine Learning
• Predictive Modeling
• Statistical Modeling
Deep Learning
• ANN
• CNN
Frameworks
• TensorFlow
• PyTorch
Data Engineering
• Big Data Processing
• Feature Engineering
Deployment
• Production ML Pipelines
• Real-Time AI Systems
🎯 What We're Looking For
• Passion for Artificial Intelligence and Healthcare Innovation
• Strong mathematical and analytical skills
• Experience building production-grade AI systems
• Ability to solve complex business problems
• Strong communication and collaboration skills
• Interest in applying AI to real-world healthcare challenges
• Growth mindset and continuous learning attitude
🌟 Why Join Axtria?
• Work with a global leader in Life Sciences Analytics
• Build AI solutions impacting millions of patients worldwide
• Exposure to cutting-edge AI and Agentic AI technologies
• Opportunity to work on large-scale enterprise AI platforms
• Collaborative and innovation-driven environment
• Career growth opportunities in AI and Healthcare
• Work alongside industry-leading AI experts and scientists
• Solve meaningful real-world healthcare challenges
📩 How to Apply
Interested candidates can share their updated resume at:
📢 Note
Only shortlisted candidates will be contacted for the further recruitment process.
🎯 Key Responsibilities
- ✓ Design, develop, and deploy advanced AI/ML models for Life Sciences applications
- ✓ Build predictive modeling solutions using machine learning and deep learning techniques
- ✓ Develop and optimize deep learning architectures including ANN and CNN models
- ✓ Design scalable, production-grade machine learning pipelines
- ✓ Build real-time AI systems and intelligent decision-making platforms
- ✓ Develop AI-powered commercial and clinical analytics solutions
- ✓ Collaborate with business, product, and domain experts
- ✓ Optimize model performance, scalability, and production deployment
- ✓ Work on large-scale structured and unstructured healthcare datasets
- ✓ Implement enterprise-grade AI solutions using modern cloud and ML technologies
💡 Required Qualifications & Skills
Frequently Asked Questions
Q1: Is Life Sciences experience mandatory?
A: No, but experience in Pharma or Life Sciences is highly preferred.
Q2: What experience level is required?
A: Candidates with 4–12 years of relevant AI/ML experience are eligible.
Q3: Which deep learning frameworks are required?
A: TensorFlow or PyTorch experience is mandatory.
Q4: Is PySpark experience necessary?
A: Yes, hands-on experience with PySpark is expected.
Q5: Are immediate joiners preferred?
A: Yes, immediate joiners will be given preference.
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