Senior_Expert (AI_Engineering)
Novartis is hiring a Senior_Expert (AI_Engineering) in Hyderabad, India. Level rates it ; you can apply on Novartis.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Some of the work can be done remotely, according to the posting.
- The posting mentions PyTorch, JAX and Python among its tools and skills.
- Novartis has 879 other open roles on Level.
- Posted in the last few days.
AI in this role
Design, train, and deploy advanced machine learning models and scalable AI inference pipelines for drug discovery.
Job Description Summary
Job Title: Senior Expert (AI-Engineering)Location: Hyderabad, India
#LI-Hybrid
Relocation Support: Yes
Imagine shaping how breakthrough medicines are discovered by bringing cutting-edge AI from concept to real-world application. As a Senior Expert in AI-Engineering, you will sit at the critical intersection of innovation and delivery—transforming advanced machine learning models into scalable, reliable solutions that accelerate drug discovery. Collaborating with leading scientists and AI experts, you will drive the translation of pioneering research into impactful tools, ensuring models are reproducible, efficient, and ready to solve complex biomedical challenges. This is an opportunity to directly influence how modern AI reshapes scientific discovery and improves patient outcomes.
Job Description
Key Responsibilities
- Design and train advanced machine learning models for drug discovery, including deep learning and graph-based architectures
- Own end-to-end model lifecycle from problem definition to production deployment and continuous improvement
- Conduct rigorous benchmarking, validation, and performance evaluation against scientific and business objectives
- Deploy scalable, reliable model inference services meeting latency, throughput, and cost requirements
- Build automated training, retraining, and monitoring pipelines including model drift detection mechanisms
- Optimize models and pipelines for performance, reliability, and scalability across production environments
- Establish and promote engineering best practices for reproducibility, testing, and deployment standards
- Collaborate with cross-functional teams to translate research innovations into production-ready AI solutions
- Partner with scientific experts to validate models against biological and chemical benchmarks
- Mentor teams and contribute to raising engineering excellence across the AI for Research organization
Essential Requirements
- Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact
- Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization
- Proven experience fine-tuning and deploying large pre-trained and foundation models including language and scientific models
- Strong understanding of model evaluation including benchmarking, cross-validation, and performance across data distributions
- Experience with distributed training and large-scale computing environments for high-performance model training
- Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance
- Experience with MLOps practices including experiment tracking, model versioning, reproducibility, and cloud deployment
- Strong problem-solving, collaboration, and communication skills with ability to drive engineering excellence in complex environments
Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Accessibility and accommodation
Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message
Skills Desired
Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Logistic Regression Model (Inactive), Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai (Inactive), Pandas (Python) (Inactive), Python (Programming Language), R Programming, Stakeholder Engagement, Statistical Analysis, Structured Query Language (SQL), Time Series AnalysisHow we rate this
Senior_Expert (AI_Engineering) at Novartis rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, ML Ops, AI Evaluation, NLP, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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