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Job Description:
3M Health Care is now Solventum
At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue.
We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you.
As a Senior Machine Learning Engineer, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world.
Here, you will make an impact by:
- Collaborating cross-functionally with domain experts, data scientists, and stakeholders to translate business requirements to technical requirements
- Implementing automated pipelines for data processing and the training, evaluation and deployment of deep learning or LLM models including Agentic AI
- Designing scalable infrastructure for model training and inference, both in the cloud and on-premises
- Setting up monitoring to enable the implementation proactive countermeasures for model degradation
- Enabling data privacy and compliance with healthcare regulations such as GDPR and HIPAA during model development and deployment
Your Skills and Expertise
To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications:
- Master's degree or PhD in computer science, mathematics, OR related fields or Bachelor’s degree with at least 5 years of experience
AND
In addition to the above requirements, the following are also required:
- Experience creating engineering solutions that support an AI / ML model’s lifecycle including data ingestion, training, evaluation, and deployment
- Familiarity with a cloud provider, preferably AWS
- Proficiency in large-scale data processing technologies, such as Hadoop and Spark
- Hands-on experience with scalable model deployment, e.g., using Docker and Kubernetes
- Capability of providing maintainable and reusable code including source control with Git, unit and integration testing and a solid knowledge of CI/CD concepts
Additional qualifications that could help you succeed even further in this role include:
- Solid understanding of Machine Learning methods
- Familiarity with the integration of LLMs and Agentic AI into real-world software solutions, for example via MCP
- Demonstrated ability of working in interdisciplinary environments
Work location: Dublin, Ireland
Work type: Hybrid
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).
Supporting Your Well-being
Solventum offers many programs to help you live your best life – both physically and financially. To ensure competitive pay and benefits, Solventum regularly benchmarks with other companies that are comparable in size and scope.
Diversity & Inclusion
(*) We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, gender, sexual orientation, age, civil status, disability, family status, or membership of the travelling community.
Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers.
Please note that all email communications from Solventum regarding job opportunities with the company will be from an email with a domain of @solventum.com. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains.
Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly.
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