Abbott

AI Platform Engineer

Abbott • $61K — $122K *
Madison, WI 53711In-Person
Information Technology
Less than 5 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, AI/ML, or related field, or equivalent experience.
  • 3+ years of experience in production software, focusing on ML/AI infrastructure.
  • Strong proficiency in Python and software engineering practices.
  • Experience managing the ML model lifecycle from training to monitoring.
  • Familiarity with Kubernetes for containerized workloads, preferably on AWS.

Responsibilities

  • Build and maintain data and training pipelines for ML and LLM workloads.
  • Implement automated evaluation and promotion gates for model production.
  • Automate the entire model lifecycle using CI/CD and GitOps methodologies.
  • Operate production model-serving infrastructure with optimization and autoscaling.
  • Manage GPU infrastructure for efficient training and inference workloads.
  • Instrument platform and models for logging, monitoring, and cost tracking.
  • Develop developer-facing interfaces like APIs and documentation for ease of use.

Benefits

  • Opportunity to work on impactful technology in the healthcare sector.
  • Hands-on experience with cutting-edge ML and generative AI platforms.
  • Participation in a culture that emphasizes innovation and teamwork.
  • Value-driven environment aligning with personal and professional integrity.
  • Potential for career growth within a well-respected organization.
Full Job Description
JOB DESCRIPTION:

Position Overview

The AI Platform Engineer builds and operates the machine learning and generative AI platform used by teams across Abbott Cancer Diagnostics. You'll own the full model lifecycle in production - data and feature pipelines, training and experimentation, evaluation and promotion, serving, and monitoring - along with the platform services, compute and tooling underneath it. This is hands-on infrastructure work backed by solid platform engineering practice: making inference fast and cheap, making the path from experiment to production repeatable and auditable, and shipping interfaces other engineers can build on - in support of software that ultimately reaches patients.

Essential Duties
Include, but are not limited to, the following:
  • Build and maintain data, feature, and training pipelines for ML and LLM workloads - ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model.
  • Implement automated evaluation and promotion gates - performance benchmarks, regression checks, and validation criteria that determine whether a model advances toward production.
  • Automate the model lifecycle end to end through CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback.
  • Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling, and low-latency serving across multiple model formats and runtimes.
  • Architect and manage GPU infrastructure - scheduling, autoscaling, resource isolation, and utilization efficiency for training and inference workloads.
  • Instrument the platform and the models on it - structured logging, telemetry, drift detection, and cost tracking - and build the triggers and pipelines that close the loop into retraining and revalidation.
  • Extend model, dataset, and artifact registries, metadata systems, and versioning so every deployed model has a traceable, auditable history.
  • Build the developer-facing surface of the platform: APIs, SDK components, templates, documentation, and runbooks that make it self-service, backed by well-tested code and active participation in design and code review.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Maintain regular and reliable attendance.
  • Act with an inclusion mindset and model these behaviors for the organization.


Minimum Qualifications
  • Bachelor's degree in Computer Science, Engineering, AI/ML, or a related field; or equivalent practical experience.
  • 3+ years building and operating production software, including significant work on ML or AI infrastructure.
  • Strong Python, including software engineering fundamentals - automated testing, code review, and designing code others will read and extend.
  • Experience with the ML model lifecycle: pipelines that carry a model from training through evaluation, deployment, monitoring, and retraining.
  • Kubernetes experience - deploying, scaling, and debugging containerized workloads on a major cloud provider (AWS preferred).
  • Experience with CI/CD, GitOps-based delivery, and infrastructure automation.


Preferred Qualifications
  • ML workflow orchestration and experiment tracking (for example Kubeflow, Argo Workflows, Airflow, MLflow, or Weights & Biases).
  • GPU infrastructure at scale: scheduling, multi-tenancy and resource isolation, autoscaling, and inference optimization such as quantization, batching, or graph compilation (for example ONNX Runtime or TensorRT).
  • Feature stores, data versioning, or dataset lineage tooling.
  • Progressive delivery for models - canary, shadow, or A/B deployment and automated rollback.
  • Model monitoring and drift detection, including automated retraining triggers.
  • Model governance and reproducibility practices: lineage tracking, audit trails, and approval workflows.
  • Kubernetes-native serverless and event-driven autoscaling (for example Knative or KEDA).
  • Experience building APIs or shared libraries consumed by other engineering teams.
  • Production experience in an additional systems language such as Go or Java.
  • Fine-tuning foundation models, or building distributed training pipelines.
  • Experience delivering software in a regulated environment (HIPAA, CLIA, GxP, SOC 2).


The base pay for this position is
$61,300.00 - $122,700.00
In specific locations, the pay range may vary from the range posted.

JOB FAMILY:
Product Development

DIVISION:
ONCO Cancer Diagnostics

LOCATION:
United States > Madison : 5505 Endeavor Ln

ADDITIONAL LOCATIONS:

WORK SHIFT:
Standard

TRAVEL:
Yes, 10 % of the Time

MEDICAL SURVEILLANCE:
No

SIGNIFICANT WORK ACTIVITIES:
Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday)

About Abbott

Abbott Careers

Joining Abbott means becoming part of a globally diverse team dedicated to making a lasting impact on human health. As a leader in healthcare innovation, Abbott provides a dynamic workplace where careers flourish through growth, leadership, and diversity training.

Opportunities at Abbott

Explore a world of opportunities with our team. Whether you're seeking job opportunities in engineering, marketing, research, or healthcare, Abbott offers a variety of positions that allow professionals to grow their careers. Our commitment to diversity and innovation is evident in every aspect of our work, fostering an inclusive culture that values each team member's contribution.

Work You'll Do

At Abbott, every role contributes to our mission of helping people live fuller lives through better health. From groundbreaking research in medical devices to advancements in pharmaceuticals, our team is at the forefront of healthcare innovation. By joining Abbott, you are not just accepting a job; you are embarking on a path of professional and personal growth.

Internship Programs

Kickstart your career with an Abbott internship. Our programs provide invaluable industry experience and a chance to develop essential skills in a real-world setting. Interns at Abbott work on projects that matter, gaining the experience and knowledge necessary to succeed in their future careers.

Professional Development

Abbott is dedicated to the continuous professional development of its employees. With access to cutting-edge technology, leadership programs, and diversity training, our team members are equipped to lead and innovate within the healthcare industry. We support your career journey with robust training programs, mentorship, and opportunities for networking and professional growth.

Benefits and Culture

Our employees enjoy comprehensive benefits designed to support their life and well-being. From health insurance to retirement plans, we ensure our team has everything they need to thrive. Abbott's culture is built on a foundation of respect and integrity, united by a shared commitment to improving health outcomes.

Join Our Team

Discover the impact you can make with a career at Abbott. We are hiring individuals who are passionate, curious, and driven to lead. Search open positions that match your skills and interests on our Jobs page. Prepare your resume, sharpen your interview skills, and get ready to join a team that's at the cutting edge of healthcare solutions.

Stay Connected

Keep up to date with career tips, industry insights, and company news—all from the people who work here. Subscribe to our Careers Blog and personalize your subscription to receive job alerts and insider tips tailored to your preferences.

Explore Abbott

With a commitment to improving life through innovation, leadership, and diversity, Abbott is a place where you can fulfill your potential. See what exciting and rewarding opportunities await at Abbott by exploring our career opportunities today.

SEARCH ABBOTT JOBS

Join us in our mission to make the world a healthier place through innovation, leadership, and diversity. Your journey to a fulfilling career at Abbott starts here.
Learn more about Abbott
Size
113,000 employees
Market Cap
$189 billion
Industry
Healthcare
Net Income
$4.4 billion
Founded
1944
5 Year Trend
+15.6%
Revenue
$34.6 billion
NASDAQ
ABT
* Ladders Estimates

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