ML Expert Scientific Computing

1 week ago

Cambridge, United States Bayer Full time
At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

ML Expert Scientific Computing

The Applied Machine Learning Group strives to accelerate the drug development process through the application of machine learning algorithms. We are a member of the larger DS&AI group and are tasked with developing best-in-class machine learning models to improve R&D (Research & Development) processes using a data-driven approach.

This role will lead to the strategic application of machine learning across R&D. We are seeking an experienced and innovative Expert in Scientific Computing to join our team. The successful candidate will play a pivotal role in driving the application of machine learning and computational tools to advance drug discovery and development, with a focus on scientific computing and related activities. Additionally, the candidate will actively support our ongoing efforts to modernize the practice of Data Science and contribute to the development of a robust Data Science Ecosystem.

OUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Machine Learning Expert for Scientific Computing, are to:
  • Strategic leadership in Scientific Computing for scalable and maintainable machine learning and analytics, with a focus on HPC environments and cloud platforms;
  • Driving strategic development and implementation of machine learning applications in high-stakes, innovation-driven environments;
  • Implementation of best practices for Analytics infrastructure, including technologies like Kubernetes and Docker, to support scalable machine learning services;
  • Focus on auditability, versioning, and data security in model development, and selecting appropriate cloud and on-premises infrastructure for machine learning model deployment;
  • Oversight of software lifecycle management to ensure integrity and quality of ML applications from development through deployment and maintenance;
  • Utilization of Agile and Scrum practices for efficient cross-functional collaboration and alignment with project goals and timelines;
  • Innovation and problem-solving in high-throughput data environments to advance scientific research and development;
  • Management of Analytics lifecycle, particularly in drug discovery settings, and implementation of predictive models for target validation and compound screening;
  • Active support for modernizing Data Science practices and contributing to the development of a robust Data Science Ecosystem;
  • The primary location for this role is either Whippany, NJ, or Cambridge, MA.
  • Visa sponsorship may be offered for this role.


WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:
  • Education and experience in Scientific computing, MLOps and understanding of software engineering role with a focus on creation of scalable data workflow to support ML model development, with an emphasis on drug discovery preferred.
  • Extensive expertise in object-oriented programming, cloud computing, database systems, and building containers and Kubernetes/EKS for ML system maintenance.
  • Familiarity with data-oriented workflow orchestration frameworks, software testing, benchmarking, CI/CD processes, and omics technologies.
  • Highly self-motivated with exceptional analytic abilities and scientific rigor, aspiring to scientific excellence.
  • Capable of effectively presenting complex topics and exhibiting leadership potential through excellent communication and soft skills.
  • Demonstrated track record of strategic leadership and effective team management in an innovation-driven field.
  • Proven ability to apply MLOps principles for scalability, reproducibility, and maintainability of machine learning models, with experience in navigating HPC environments and cloud platforms.


Preferred Experience:
  • Familiarity of the drug discovery process, encompassing a comprehensive grasp of biological concepts such as gene regulation, molecular interactions, cellular pathways, and omics technologies.
  • Experience with regulatory considerations for computational tools in pharmaceutical research.
  • D emonstrated ability to adapt and thrive in a rapidly evolving technological landscape.
  • 10+ years of industry experience.
  • 4+ years’ experience specifically in scientific computing and its application within Pharmaceuticals.


Bayer will be accepting applications for this role through 26 August 2024.

#LI-US
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

Bayer is an E-Verify Employer. Location: United States : Massachusetts : Cambridge || United States : New Jersey : Whippany Division: Pharmaceuticals Reference Code: 825243 Contact Us Email: hrop_usa@bayer.com

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