Our Base Pay Range for this position €72,000 - €120,000 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
You will provide technical leadership across the full AI lifecycle, from experimentation and model development through deployment, observability, governance, and continuous improvement.
Lead development and deployment of enterprise AI/ML and LLM solutions
Build ML pipelines on Azure Machine Learning and Azure Databricks
Establish MLOps and LLMOps practices including CI/CD, versioning, and monitoring
Implement model observability, drift detection, and reliability engineering
Mentor engineers and move prototypes into reliable production systems
You will provide technical leadership across the full AI lifecycle, from experimentation and model development through deployment, observability, governance, and continuous improvement.
Lead the design, development, deployment, and operation of enterprise-scale AI/ML and LLM solutions.
Build and productionize machine learning pipelines using Azure Machine Learning, Azure Databricks, and cloud-native services.
Establish and enhance MLOps and LLMOps practices including CI/CD, model versioning, automated testing, monitoring, and governance.
Implement model observability, performance monitoring, drift detection, and reliability engineering practices.
Partner with data scientists and product teams to transition prototypes into reliable production systems.
7+ years of experience designing, building, and supporting machine learning solutions in enterprise environments.
Experience developing and deploying Generative AI and Large Language Model (LLM) solutions.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience.
Experience with Azure AI Foundry, prompt engineering, evaluation frameworks, and AI guardrails.
Experience deploying machine learning models into production cloud environments.
Knowledge of LLMOps practices, RAG architectures, model evaluation, and AI observability.
Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 7
Early. Similar jobs usually come down between day 8 and day 76.
At McKesson, jobs usually come down by about day 31.
From 5,460 similar postings that came down, and 185 of McKesson’s. Coming down is not always a hire.
45 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience. - Strong software engineering experience with Python and modern application development practices. - Experience deploying machine learning models into production cloud environments.
- Lead the design, development, deployment, and operation of enterprise-scale AI/ML and LLM solutions. - Build and productionize machine learning pipelines using Azure Machine Learning, Azure Databricks, and cloud-native services. - Establish and enhance MLOps and LLMOps practices including CI/CD, model versioning, automated testing, monitoring, and governance.
- Hands-on experience with MLOps including CI/CD pipelines, model lifecycle management, automation, and monitoring. - Experience with Azure Machine Learning, Azure Databricks, or comparable cloud-based machine learning platforms. - Experience with containerization technologies such as Docker and production deployment patterns.
- Experience developing and deploying Generative AI and Large Language Model (LLM) solutions. - Experience with Azure AI Foundry, prompt engineering, evaluation frameworks, and AI guardrails. - Knowledge of LLMOps practices, RAG architectures, model evaluation, and AI observability.
- Experience with Azure Machine Learning, Azure Databricks, or comparable cloud-based machine learning platforms. - Experience with containerization technologies such as Docker and production deployment patterns. - Ability to communicate technical concepts effectively to both technical and business stakeholders.
- Experience with Terraform or other Infrastructure-as-Code tools. - Experience with Kubernetes, AKS, distributed computing, or large-scale data processing platforms. - Familiarity with AI governance, responsible AI, security, privacy, and compliance practices.
- Knowledge of LLMOps practices, RAG architectures, model evaluation, and AI observability. - Experience with Terraform or other Infrastructure-as-Code tools. - Experience with Kubernetes, AKS, distributed computing, or large-scale data processing platforms.
Complete your application on mckesson.wd3.myworkdayjobs.com. The employer’s form will show what is required.
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Yes. We’ve followed one other Senior Specialist, Machine Learning Engineering job there since November 2026. It is still up.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.
What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.
About the Role
McKesson is seeking a Sr. Specialist, Machine Learning Engineering to design, build, and scale production-grade AI, machine learning, and generative AI solutions that deliver meaningful business impact. In this role, you will lead the development of scalable ML platforms, production pipelines, model deployment frameworks, and MLOps capabilities while partnering with cross-functional teams to solve complex business and technology challenges.
You will provide technical leadership across the full AI lifecycle, from experimentation and model development through deployment, observability, governance, and continuous improvement.
What You'll Do
Basic Requirements
Preferred Skills/Experience
Travel / Work Environment / Physical Requirements
At McKesson, we care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse employee population and ensure they are the healthiest versions of themselves.
As part of Total Rewards, we are proud to offer a competitive compensation package at McKesson. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.
Our Base Pay Range for this position
€72,000 - €120,000McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.
McKesson job postings are posted on our career site: careers.mckesson.com.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Our Base Pay Range for this position €72,000 - €120,000 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
Cork
- Travel may be required based on business needs. - Position may be remote, hybrid, or office-based depending on organizational requirements. - Must be able to perform standard computer-based work activities and communicate effectively with internal and external stakeholders.
No clear work-authorization passage found. Eligibility is unconfirmed.