Associate Director, Technical Lead (ML Engineering & Compute Platform Focus)

Posted 5 Days Ago
Be an Early Applicant
Prague, CZE
In-Office
1M-3M Annually
Senior level
Biotech • Pharmaceutical
The Role
Lead design, build, and operate hybrid ML compute platforms (on-prem HPC and AWS GPU) and MLOps pipelines. Ensure efficient, secure, cost-optimized GPU workloads, orchestration, CI/CD, and partner with data scientists and engineering teams to deliver scalable ML infrastructure.
Summary Generated by Built In

Salary Range:

Kč1,354,220.00 - Kč2,514,980.00

Job Description Summary

Are you passionate about building the ML platforms, compute environments, and AI capabilities that power scientific discovery at scale? This is a unique opportunity to join a newly created Product Technology & Engineering team in Prague and help shape the future of ML engineering across BR Data & Digital. As Technical Lead (ML Engineering & Compute Platform Focus), you will provide hands-on architectural and technical leadership to design, build, and operate the ML engineering and compute platforms that power scientific discovery at scale. From on-premises HPC clusters to cloud-based GPU compute on AWS, you will ensure data scientists and ML engineers have reliable, scalable, and high-performance infrastructure to train, deploy, and operate machine learning solutions, while embedding modern MLOps practices and AI-driven engineering approaches across the full ML lifecycle.
Location: Prague, Czech Republic #LI-Hybrid
This role is based in Prague, Czech Republic. Novartis is unable to offer relocation support for this role: please only apply if this location is accessible for you.

Job Description

Responsibilities:

  • Lead the design, delivery, and operation of ML compute platforms spanning on-premises HPC clusters and cloud-based GPU infrastructure on AWS.

  • Support implementation of MLOps pipelines across model training, experiment tracking, packaging, deployment, and production monitoring.

  • Ensure compute resources are reliable, efficiently utilised, and cost-optimised.

  • Manage job scheduling, GPU resource allocation, and workload orchestration across hybrid environments.

  • Champion AI-driven engineering transformation across the team, embedding AI tools into architecture, code generation, code review, CI/CD, and testing workflows.

  • Embed security at every layer of the ML engineering lifecycle, enforcing OAuth2, OIDC, SAML, zero-trust principles, and secrets management.

  • Partner closely with data scientists, ML engineers, delivery leads, architects, and operations teams to translate ML workload requirements into robust platform capabilities.

  • Manage technical dependencies and ensure platform delivery stays aligned and on track within time-bound product initiatives.

  • Contribute to a coherent technical architecture across the broader BR Data & Digital product portfolio.

  • Foster a team-before-self culture of urgency, quality, and continuous improvement.

Essential for the role:

  • 7+ years of hands-on experience in ML engineering, MLOps, or compute platform engineering in complex, large-scale environments.

  • Deep expertise in MLOps practices and tooling, including ML pipeline orchestration, experiment tracking, model registry, model serving, and production monitoring and drift detection.

  • Strong experience with HPC and compute platform engineering, including GPU cluster management, job scheduling, and high-throughput workload orchestration in on-premises environments.

  • Deep expertise in AWS cloud compute for ML, including GPU instances, AWS Batch, Amazon SageMaker, and AWS ParallelCluster for scalable training and inference workloads.

  • Strong experience with containerisation for ML workloads, including Docker, NVIDIA Container Toolkit, and Kubernetes with GPU node management.

  • Strong security mindset with practical experience in OAuth2, OIDC, SAML, and secrets management.

  • Active practitioner of AI-driven engineering, using AI tools to accelerate architecture decisions, code generation, code review, CI/CD, and testing.

  • Proficiency in Python and/or another modern programming language, with the ability to lead and review code across a cross-functional engineering team.

Desirable for the role:

  • Hands-on experience with NVIDIA DGX systems or similar high-density GPU computing infrastructure.

  • Experience with distributed training frameworks and large-scale model training.

Benefits & Rewards:

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

Expected Annual Base Salary Range for role: 1,354,220.00 to 2,514,980.00 CZK

The base 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.

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 minimum 14 weeks paid parental leave.

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 & 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 all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to receive more detailed information about the essential functions of a position, please send an email to [email protected] and let us know the nature of your request and your contact information. Please include the job requisition number in your message. 


 

Skills Desired

Algorithms, Computer Programming, Computer Science, Computer Vision, Data Science, People Management, Waterfall Model

Skills Required

  • 7+ years hands-on experience in ML engineering, MLOps, or compute platform engineering in large-scale environments
  • Deep expertise in MLOps practices and tooling including ML pipeline orchestration, experiment tracking, model registry, model serving, and production monitoring
  • Strong experience with HPC and compute platform engineering, GPU cluster management, job scheduling, and high-throughput workload orchestration (on-premises)
  • Deep expertise in AWS cloud compute for ML including GPU instances, AWS Batch, Amazon SageMaker, and AWS ParallelCluster
  • Strong experience with containerisation for ML workloads including Docker, NVIDIA Container Toolkit, and Kubernetes with GPU node management
  • Practical experience with OAuth2, OIDC, SAML, and secrets management (security for ML lifecycle)
  • Active practitioner of AI-driven engineering, using AI tools for architecture, code generation, code review, CI/CD, and testing
  • Proficiency in Python and/or another modern programming language
  • Hands-on experience with NVIDIA DGX systems or similar high-density GPU computing infrastructure
  • Experience with distributed training frameworks and large-scale model training

Novartis Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Novartis and has not been reviewed or approved by Novartis.

  • Healthcare Strength Pay and benefits are described as a strong overall package, supported by medical, dental, and vision insurance alongside FSAs/HSAs and disability and life coverage. Mental-health support is reinforced through an employee assistance program with psychological support and a network of mental health first aiders.
  • Retirement Support Retirement support is positioned as a standout element, with an automatic company contribution plus dollar-for-dollar matching in the 401(k). Additional retirement funding is described through an age-based defined contribution program and access to an employee share purchase plan discount.
  • Parental & Family Support Family-related benefits are framed as robust, including a global minimum of paid parental leave for new parents following birth or adoption. Added supports include domestic partner coverage, dependent-care resources, and benefits such as adoption assistance and child/elder care options.

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The Company
HQ: Basel
110,000 Employees
Year Founded: 1996

What We Do

Novartis is an innovative medicines company. Every day, working to reimagine medicine to improve and extend people’s lives so that patients, healthcare professionals and societies are empowered in the face of serious disease. Our medicines reach more than 250 million people worldwide.

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