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Senior Staff GenAI and ML Ops Engineer

GE Healthcare

Software and Technology Jobs

Senior Staff GenAI and ML Ops Engineer

full-timePosted: Jan 14, 2026

Job Description

Job Description Summary

Role Overview
GE HealthCare’s Chief Data and Analytics Office (CDAO) delivers innovative data, insights, and AI solutions across the organization. Our Enterprise AI team drives a diverse portfolio of Machine Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) initiatives by combining agile execution with industry-leading methods and tools.
As a GenAI/ML Ops Engineer, you will be at the forefront of operationalizing advanced Machine Learning and Generative AI solutions. You will design, deliver, and maintain robust development and deployment pipelines for high-impact AI applications across key business domains within GE HealthCare — including Finance, Commercial, Supply Chain, Quality, Operational Excellence, Lean, and Manufacturing.
We are seeking a highly skilled and motivated engineer experienced in ML and GenAI operations, software development, and AI architecture to join our dynamic and growing team.

Job Description

Core Responsibilities

  • Develop and operationalize ML and GenAI pipelines to enable scalable, reliable, and secure deployment of AI models across GE HealthCare’s enterprise landscape.

  • Automate model lifecycle management, including model versioning, continuous integration (CI/CD), testing, deployment, observability and monitoring, and governance in alignment with enterprise standards.

  • Partner with IT and cloud teams to optimize infrastructure for AI workloads across hybrid and multi-cloud environments (AWS, Azure)

  • Collaborate with cross-functional teams — including data scientists, software engineers, architects, and domain experts — to ensure smooth end-to-end delivery of AI solutions.

  • Integrate Generative AI capabilities (e.g., LLMs, multimodal models) into business workflows, enhancing automation, productivity, and decision intelligence.

  • Conduct research and proof-of-concepts to evaluate emerging tools, frameworks, and architectures for GenAI and ML Ops (e.g., LangChain, MLflow, Kubeflow, MS Copilot, OpenAi Agent Builder)

  • Mentor and guide data science and engineering teams on best practices in productionizing AI models and managing their lifecycle.

  • Promote a culture of innovation, collaboration, and continuous improvement within the Enterprise AI team.


Experience & Qualifications

  • PhD or Master’s degree in Computer Science, Data Science, Engineering, or a related discipline with a strong focus on Machine Learning, Deep Learning, or AI Operations.

  • Overall 8+ years of experience

  • 1–3 years of hands-on experience in developing, deploying, and maintaining ML/AI development pipelines and applications in enterprise environments.

  • Knowledge of API development and orchestration frameworks (FastAPI, Flask, Airflow).

  • Demonstrated expertise in MLOps / GenAIOps tools and frameworks (e.g., MLflow, SageMaker, Bedrock , LangSmith, LangGraph).

  • Experience in Python, cloud platforms (AWS, Azure), and open-source data science tools (Jupyter, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, Scikit-learn).

  • Understanding of containerization, CI/CD, and DevOps practices (Docker, Kubernetes, GitHub Actions, Jenkins).

  • Experience with data preprocessing, feature engineering, and model evaluation in real-world, large-scale environments.

  • Experience with LLMs and generative AI models, including transformers, diffusion models, self-supervised learning, and prompt engineering.

  • Proven ability to translate research and prototypes into scalable enterprise-grade solutions.

  • Excellent communication, collaboration, and stakeholder management skills, with the ability to influence both technical and executive audiences.

  • Curiosity and drive for continuous learning, staying current with advances in GenAI, MLOps, and AI infrastructure technologies.

  • Problem-solving, debugging, and analytical skills, with clear and persuasive communication to technical audiences.


Inclusion and Diversity

GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support

Additional Information

Relocation Assistance Provided: No

Locations

  • Bengaluru, Karnātaka, India

Salary

Estimated Salary Rangemedium confidence

40,000 - 75,000 INR / yearly

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • ML and GenAI pipelines developmentintermediate
  • MLOps / GenAIOps tools (MLflow, SageMaker, Bedrock, LangSmith, LangGraph)intermediate
  • Python programmingintermediate
  • Cloud platforms (AWS, Azure)intermediate
  • Containerization and CI/CD (Docker, Kubernetes, GitHub Actions, Jenkins)intermediate
  • API development (FastAPI, Flask, Airflow)intermediate
  • LLMs and generative AI modelsintermediate
  • Data preprocessing and feature engineeringintermediate

Required Qualifications

  • PhD or Master’s degree in Computer Science, Data Science, Engineering, or related discipline (experience)
  • 8+ years of overall experience (experience)
  • 1–3 years of hands-on experience in ML/AI pipelines (experience)
  • Experience with open-source data science tools (TensorFlow, PyTorch, Scikit-learn) (experience)

Responsibilities

  • Develop and operationalize ML and GenAI pipelines for scalable deployment
  • Automate model lifecycle management including versioning, CI/CD, testing, observability, monitoring, and governance
  • Partner with IT and cloud teams to optimize infrastructure for AI workloads across AWS and Azure
  • Collaborate with cross-functional teams for end-to-end AI solution delivery
  • Integrate Generative AI capabilities (LLMs, multimodal models) into business workflows
  • Conduct research and proof-of-concepts on emerging GenAI and ML Ops tools
  • Mentor data science and engineering teams on productionizing AI models

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GE Healthcare logo

Senior Staff GenAI and ML Ops Engineer

GE Healthcare

Software and Technology Jobs

Senior Staff GenAI and ML Ops Engineer

full-timePosted: Jan 14, 2026

Job Description

Job Description Summary

Role Overview
GE HealthCare’s Chief Data and Analytics Office (CDAO) delivers innovative data, insights, and AI solutions across the organization. Our Enterprise AI team drives a diverse portfolio of Machine Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) initiatives by combining agile execution with industry-leading methods and tools.
As a GenAI/ML Ops Engineer, you will be at the forefront of operationalizing advanced Machine Learning and Generative AI solutions. You will design, deliver, and maintain robust development and deployment pipelines for high-impact AI applications across key business domains within GE HealthCare — including Finance, Commercial, Supply Chain, Quality, Operational Excellence, Lean, and Manufacturing.
We are seeking a highly skilled and motivated engineer experienced in ML and GenAI operations, software development, and AI architecture to join our dynamic and growing team.

Job Description

Core Responsibilities

  • Develop and operationalize ML and GenAI pipelines to enable scalable, reliable, and secure deployment of AI models across GE HealthCare’s enterprise landscape.

  • Automate model lifecycle management, including model versioning, continuous integration (CI/CD), testing, deployment, observability and monitoring, and governance in alignment with enterprise standards.

  • Partner with IT and cloud teams to optimize infrastructure for AI workloads across hybrid and multi-cloud environments (AWS, Azure)

  • Collaborate with cross-functional teams — including data scientists, software engineers, architects, and domain experts — to ensure smooth end-to-end delivery of AI solutions.

  • Integrate Generative AI capabilities (e.g., LLMs, multimodal models) into business workflows, enhancing automation, productivity, and decision intelligence.

  • Conduct research and proof-of-concepts to evaluate emerging tools, frameworks, and architectures for GenAI and ML Ops (e.g., LangChain, MLflow, Kubeflow, MS Copilot, OpenAi Agent Builder)

  • Mentor and guide data science and engineering teams on best practices in productionizing AI models and managing their lifecycle.

  • Promote a culture of innovation, collaboration, and continuous improvement within the Enterprise AI team.


Experience & Qualifications

  • PhD or Master’s degree in Computer Science, Data Science, Engineering, or a related discipline with a strong focus on Machine Learning, Deep Learning, or AI Operations.

  • Overall 8+ years of experience

  • 1–3 years of hands-on experience in developing, deploying, and maintaining ML/AI development pipelines and applications in enterprise environments.

  • Knowledge of API development and orchestration frameworks (FastAPI, Flask, Airflow).

  • Demonstrated expertise in MLOps / GenAIOps tools and frameworks (e.g., MLflow, SageMaker, Bedrock , LangSmith, LangGraph).

  • Experience in Python, cloud platforms (AWS, Azure), and open-source data science tools (Jupyter, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, Scikit-learn).

  • Understanding of containerization, CI/CD, and DevOps practices (Docker, Kubernetes, GitHub Actions, Jenkins).

  • Experience with data preprocessing, feature engineering, and model evaluation in real-world, large-scale environments.

  • Experience with LLMs and generative AI models, including transformers, diffusion models, self-supervised learning, and prompt engineering.

  • Proven ability to translate research and prototypes into scalable enterprise-grade solutions.

  • Excellent communication, collaboration, and stakeholder management skills, with the ability to influence both technical and executive audiences.

  • Curiosity and drive for continuous learning, staying current with advances in GenAI, MLOps, and AI infrastructure technologies.

  • Problem-solving, debugging, and analytical skills, with clear and persuasive communication to technical audiences.


Inclusion and Diversity

GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support

Additional Information

Relocation Assistance Provided: No

Locations

  • Bengaluru, Karnātaka, India

Salary

Estimated Salary Rangemedium confidence

40,000 - 75,000 INR / yearly

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • ML and GenAI pipelines developmentintermediate
  • MLOps / GenAIOps tools (MLflow, SageMaker, Bedrock, LangSmith, LangGraph)intermediate
  • Python programmingintermediate
  • Cloud platforms (AWS, Azure)intermediate
  • Containerization and CI/CD (Docker, Kubernetes, GitHub Actions, Jenkins)intermediate
  • API development (FastAPI, Flask, Airflow)intermediate
  • LLMs and generative AI modelsintermediate
  • Data preprocessing and feature engineeringintermediate

Required Qualifications

  • PhD or Master’s degree in Computer Science, Data Science, Engineering, or related discipline (experience)
  • 8+ years of overall experience (experience)
  • 1–3 years of hands-on experience in ML/AI pipelines (experience)
  • Experience with open-source data science tools (TensorFlow, PyTorch, Scikit-learn) (experience)

Responsibilities

  • Develop and operationalize ML and GenAI pipelines for scalable deployment
  • Automate model lifecycle management including versioning, CI/CD, testing, observability, monitoring, and governance
  • Partner with IT and cloud teams to optimize infrastructure for AI workloads across AWS and Azure
  • Collaborate with cross-functional teams for end-to-end AI solution delivery
  • Integrate Generative AI capabilities (LLMs, multimodal models) into business workflows
  • Conduct research and proof-of-concepts on emerging GenAI and ML Ops tools
  • Mentor data science and engineering teams on productionizing AI models

Target Your Resume for "Senior Staff GenAI and ML Ops Engineer" , GE Healthcare

Get personalized recommendations to optimize your resume specifically for Senior Staff GenAI and ML Ops Engineer. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Senior Staff GenAI and ML Ops Engineer" , GE Healthcare

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Answer 10 quick questions to check your fit for Senior Staff GenAI and ML Ops Engineer @ GE Healthcare.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.