At Cardinal Health's Artificial Intelligence Center of Excellence (AI CoE), we are pushing the boundaries of healthcare with cutting-edge Data Science and Artificial Intelligence (AI). Our mission is to leverage the power of data to create innovative solutions that improve patient outcomes, streamline operations, and enhance the overall healthcare experience.
We are seeking a highly motivated and skilled Full Stack Machine Learning Engineer to join our growing team. You will play a key role in developing, deploying, and integrating impactful AI solutions that address critical business challenges. You will be responsible for building end-to-end AI-powered/driven systems, combining your expertise in machine learning, software engineering, and user interface development.
**Why Join Cardinal Health's AI CoE?**
+ Make a Real Difference: Contribute to cutting-edge solutions that improve patient care, enhance healthcare operations, and drive positive change in the industry.
+ Work with a Passionate Team: Join a team of highly skilled data scientists and engineers who are committed to pushing the boundaries of AI in healthcare.
+ Grow and Develop: Access opportunities for professional growth, mentorship, and development within a dynamic and innovative environment.
**Responsibilities:**
+ Explore and Implement Generative AI Solutions: You will work with the team to explore and implement Generative AI (GenAI) technologies like Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. This may involve tasks like building prompt engineering strategies, integrating LLMs with relevant healthcare data, and evaluating the performance of GenAI models in various applications.
+ Develop and Deploy Machine Learning Models: You will design, build, and deploy machine learning models to tackle a variety of problems including forecasting, classification, risk prediction, and more. This will involve leveraging your expertise in Python, machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, and cloud platforms like Google Cloud Platform (GCP).
+ Contribute to GenAI/ML Pipeline Development: You will work collaboratively with other engineers and data scientists to build robust and scalable GenAI / ML pipelines, ensuring data quality, model training, and deployment efficiency. This may include using tools like Docker, Kubernetes, and Airflow.
+ Build and Maintain APIs for Machine Learning Services: You will design, develop, and maintain RESTful APIs to integrate your ML models and GenAI solutions with existing systems, ensuring efficient data flow and communication between different components of the system.
+ Contribute to User Interface Development: You will work collaboratively with the team to design and develop user interfaces (UI) for applications that leverage your ML models and GenAI solutions. You will have the opportunity to utilize front-end technologies like HTML, CSS, JavaScript, and potentially frameworks like React to create intuitive and user-friendly interfaces.
+ Collaborate with Business Stakeholders: You will work closely with key business stakeholders to understand their needs and translate them into actionable AI-driven solutions. You will help bridge the gap between technical expertise and business requirements.
+ Stay Abreast of Emerging Technologies: You will continuously explore and learn about the latest advancements in AI, particularly in the areas of ML, GenAI, LLMs, and RAG technologies, to ensure that we are leveraging the most effective approaches.
**Qualifications:**
+ Bachelor's degree in Computer Science or related field, or equivalent work experience, preferred
+ 2-4 years of experience, preferred
+ Machine Learning Fundamentals: Strong understanding of machine learning algorithms, techniques, and their applications.
+ Programming Proficiency: Proficient in Python and comfortable working with machine learning libraries like Scikit-learn, TensorFlow, PyTorch, or similar, preferred.
+ Cloud Computing Experience: Experience with cloud platforms like GCP, AWS, or Azure for data processing, model training, deployment, and management, preferred.
+ Data Engineering Skills: Familiarity with data engineering principles, data pipelines, and working with various data formats, preferred.
+ Full-Stack Development Skills: Experience with front-end technologies (HTML, CSS, JavaScript, potentially React) and backend technologies (Python, Node.js, etc.), as well as API development (RESTful APIs) and microservices architecture, preferred.
+ Communication and Teamwork: Excellent communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders, preferred.
+ Experience with Generative AI, LLMs, and RAG technologies, preferred.
+ Experience with CI/CD pipelines for GenAI solutions and ML models, preferred.
+ Familiarity with API development (RESTful APIs) and microservices architecture, preferred.
+ Experience working with healthcare data and understanding of HIPAA regulations, preferred.
+ Knowledge of software engineering patterns and best practices, preferred.
+ Experience with Agile development methodologies and DevSecOps principles, preferred.
**Anticipated salary range:** $79, 300 - $113,200
**Bonus eligible:** No
**Benefits:** Cardinal Health offers a wide variety of benefits and programs to support health and well-being.
+ Medical, dental and vision coverage
+ Paid time off plan
+ Health savings account (HSA)
+ 401k savings plan
+ Access to wages before pay day with myFlexPay
+ Flexible spending accounts (FSAs)
+ Short- and long-term disability coverage
+ Work-Life resources
+ Paid parental leave
+ Healthy lifestyle programs
**Application window anticipated to close:** 12/02/2024 *if interested in opportunity, please submit application as soon as possible.
The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidates geographical location, relevant education, experience and skills and an evaluation of internal pay equity.
_Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply._
_Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal_ _Opportunity/Affirmative_ _Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law._
_To read and review this privacy notice click_ here (https://www.cardinalhealth.com/content/dam/corp/email/documents/corp/cardinal-health-online-application-privacy-policy.pdf)

At Cardinal Health's Artificial Intelligence Center of Excellence (AI CoE), we are pushing the boundaries of healthcare with cutting-edge Data Science and Artificial Intelligence (AI). Our mission is to leverage the power of data to create innovative solutions that improve patient outcomes, streamline operations, and enhance the overall healthcare experience. We are seeking a highly motivated and skilled Full Stack Machine Learning Engineer to join our growing team. You will play a key role in developing, deploying, and integrating impactful AI solutions that address critical business challenges. You will be responsible for building end-to-end AI-powered/driven systems, combining your expertise in machine learning, software engineering, and user interface development. **Why Join Cardinal Health's AI CoE?** + Make a Real Difference: Contribute to cutting-edge solutions that improve patient care, enhance healthcare operations, and drive positive change in the industry. + Work with a Passionate Team: Join a team of highly skilled data scientists and engineers who are committed to pushing the boundaries of AI in healthcare. + Grow and Develop: Access opportunities for professional growth, mentorship, and development within a dynamic and innovative environment. **Responsibilities:** + Explore and Implement Generative AI Solutions: You will work with the team to explore and implement Generative AI (GenAI) technologies like Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. This may involve tasks like building prompt engineering strategies, integrating LLMs with relevant healthcare data, and evaluating the performance of GenAI models in various applications. + Develop and Deploy Machine Learning Models: You will design, build, and deploy machine learning models to tackle a variety of problems including forecasting, classification, risk prediction, and more. This will involve leveraging your expertise in Python, machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, and cloud platforms like Google Cloud Platform (GCP). + Contribute to GenAI/ML Pipeline Development: You will work collaboratively with other engineers and data scientists to build robust and scalable GenAI / ML pipelines, ensuring data quality, model training, and deployment efficiency. This may include using tools like Docker, Kubernetes, and Airflow. + Build and Maintain APIs for Machine Learning Services: You will design, develop, and maintain RESTful APIs to integrate your ML models and GenAI solutions with existing systems, ensuring efficient data flow and communication between different components of the system. + Contribute to User Interface Development: You will work collaboratively with the team to design and develop user interfaces (UI) for applications that leverage your ML models and GenAI solutions. You will have the opportunity to utilize front-end technologies like HTML, CSS, JavaScript, and potentially frameworks like React to create intuitive and user-friendly interfaces. + Collaborate with Business Stakeholders: You will work closely with key business stakeholders to understand their needs and translate them into actionable AI-driven solutions. You will help bridge the gap between technical expertise and business requirements. + Stay Abreast of Emerging Technologies: You will continuously explore and learn about the latest advancements in AI, particularly in the areas of ML, GenAI, LLMs, and RAG technologies, to ensure that we are leveraging the most effective approaches. **Qualifications:** + Bachelor's degree in Computer Science or related field, or equivalent work experience, preferred + 2-4 years of experience, preferred + Machine Learning Fundamentals: Strong understanding of machine learning algorithms, techniques, and their applications. + Programming Proficiency: Proficient in Python and comfortable working with machine learning libraries like Scikit-learn, TensorFlow, PyTorch, or similar, preferred. + Cloud Computing Experience: Experience with cloud platforms like GCP, AWS, or Azure for data processing, model training, deployment, and management, preferred. + Data Engineering Skills: Familiarity with data engineering principles, data pipelines, and working with various data formats, preferred. + Full-Stack Development Skills: Experience with front-end technologies (HTML, CSS, JavaScript, potentially React) and backend technologies (Python, Node.js, etc.), as well as API development (RESTful APIs) and microservices architecture, preferred. + Communication and Teamwork: Excellent communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders, preferred. + Experience with Generative AI, LLMs, and RAG technologies, preferred. + Experience with CI/CD pipelines for GenAI solutions and ML models, preferred. + Familiarity with API development (RESTful APIs) and microservices architecture, preferred. + Experience working with healthcare data and understanding of HIPAA regulations, preferred. + Knowledge of software engineering patterns and best practices, preferred. + Experience with Agile development methodologies and DevSecOps principles, preferred. **Anticipated salary range:** $79, 300 - $113,200 **Bonus eligible:** No **Benefits:** Cardinal Health offers a wide variety of benefits and programs to support health and well-being. + Medical, dental and vision coverage + Paid time off plan + Health savings account (HSA) + 401k savings plan + Access to wages before pay day with myFlexPay + Flexible spending accounts (FSAs) + Short- and long-term disability coverage + Work-Life resources + Paid parental leave + Healthy lifestyle programs **Application window anticipated to close:** 12/02/2024 *if interested in opportunity, please submit application as soon as possible. The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidates geographical location, relevant education, experience and skills and an evaluation of internal pay equity. _Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply._ _Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal_ _Opportunity/Affirmative_ _Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law._ _To read and review this privacy notice click_ here (https://www.cardinalhealth.com/content/dam/corp/email/documents/corp/cardinal-health-online-application-privacy-policy.pdf)

Machine Learning Engineer Cardinal Health Jobs

Full Stack Machine Learning Engineer Senior Analyst
December 3, 2024

Full Stack Machine Learning Engineer Senior Analyst
December 2, 2024

Full Stack Machine Learning Engineer Senior Analyst
November 29, 2024

Quick filters

Top companies

Machine Learning Engineer Cardinal Health Jobs

Full Stack Machine Learning Engineer Senior AnalystDecember 3, 2024

Full Stack Machine Learning Engineer Senior AnalystDecember 2, 2024

Full Stack Machine Learning Engineer Senior AnalystNovember 29, 2024

Quick filters

Top companies

Full Stack Machine Learning Engineer Senior Analyst
December 3, 2024

Full Stack Machine Learning Engineer Senior Analyst
December 2, 2024

Full Stack Machine Learning Engineer Senior Analyst
November 29, 2024