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Salary
$71k – $132k per year
Location
Hybrid (Dublin, Ireland)
Seniority
Senior · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Oct 28, 2026. Novartis scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Novartis is a Swiss pharmaceutical company created in 1996 by the merger of Ciba-Geigy and Sandoz, two Basel chemical and drug houses with roots in the nineteenth century. It has spent the past decade narrowing itself into a pure innovative medicines business, spinning off its generics arm as Sandoz in 2023 and its eye care business as Alcon in 2019, and now concentrates on cardiovascular, immunology, neuroscience and oncology, including radioligand therapies and gene therapy. Headquartered in Basel and listed in Zurich and New York, it is among the largest research spenders in the industry.

Salary Range:

€63,490.00 - €117,910.00

Job Description Summary

Job Title: Senior Expert (AI-Engineering)

Location: Dublin, Ireland

Relocation Support: This role is based in Dublin, Ireland. Novartis is unable to offer relocation support: please only apply if accessible.

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 4 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

Rewards

At Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen.

The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave.

Expected Annual Base Salary Range for role:

  • Dublin: 63,490.00 - 117,910.00 EUR Annual

The salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.

In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Further details will be provided during the application process.

Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.

Read our brochure to learn more about our global total rewards offering: https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf

Note: Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process.

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.

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 Analysis
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