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Staff AI/ML Platform Engineer

Abbott

Alameda, CAJob$114–228K/yrSeen 3w agoSeen in employer's feed 6 days ago

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At a glance

Compensation
$114–228K/yr
Location
Alameda, CA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Bachelor's degree, required

Job overview

Abbott’s Lingo team is building a health platform that combines continuous biosensor data, real-time analytics, and personalized insights. The Staff AI/ML Platform Engineer will design and build infrastructure to move machine learning models from experimentation to production across cloud and devices, connecting data pipelines to ML systems and enabling AI engineering and data science teams to deploy models reliably.

Skills & qualifications

RequiredNice to have

Skills

Azure ML SDK, requiredAzure Data Factory, requiredDatabricks, requiredMLflow, requiredKubeflow, requiredPython, requiredContainers, requiredDocker, requiredKubernetes, requiredInfrastructure as Code, requiredCloud Platforms, requiredDevOps and SRE Collaboration, requiredData Lakes, requiredStreaming Data, requiredTime-Series Data, requiredFeature Stores, requiredModel Monitoring, requiredDrift Detection, requiredAutomated Retraining, requiredRegulated Industry Experience, nice to haveValidated Software Environments, nice to haveIEC 62304, nice to haveISO 13485, nice to haveFDA AI/ML Guidance, nice to haveHIPAA, nice to haveMobile Model Deployment, nice to haveEdge Model Deployment, nice to haveLLM Operations, nice to havePrompt Management, nice to haveEvaluation Pipelines, nice to haveInference Cost Control, nice to haveHigh-Volume IoT Data, nice to haveWearable Sensor Data, nice to have

Qualifications

Bachelor's in Engineering, Mathematics, Computer Science, or Related Field, required8+ Years Software or ML Engineering Experience, required3+ Years Deploying ML Models on Mobile or Embedded Devices, requiredMaster's or PhD in Computer Science, Machine Learning, or Related Field, nice to have

Benefits

Medical Insurance
401(k) Match
Tuition Assistance

Full job description

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries.

At Lingo, we’re building a groundbreaking health platform that combines continuous biosensor data, real-time analytics, and personalized insights to help people live fuller, longer, and healthier lives. Our systems ingest millions of sensor readings daily, powering experiences for consumers and partners worldwide, with the reliability and scalability of cloud-native, enterprise-grade platforms.

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:

THE OPPORTUNITY

This Staff AI/ML Platform Engineer position can work out of Alameda, CA location.

As Staff AI/ML Platform Engineer, you will design and build the platform that takes machine learning models from experiment to production, safely and repeatably, across cloud and device. You will connect our existing data lake and ETL pipelines to ML infrastructure and enable both the AI engineering and data science teams to ship with confidence.

You will work closely with data engineering, DevOps and SRE, data science, security, quality, and regulatory teams, so a high level of technical judgement and professionalism is required.

What You'll Work On

  • Define the architecture and roadmap for the AI platform, feature store, training pipelines, model registry, deployment, and serving.

  • Partner with the data engineering team to define the boundary between curated data and ML features and ensure lineage from raw sensor data to model output.

  • Enable data scientists to self-serve training and deployment through templates, tooling, and documentation.

  • Extend the existing CI/CD pipelines with model-specific stages, including automated testing, validation gates, and approval workflows aligned with design controls.

  • Implement model monitoring for performance, data drift, and sensor data quality on the shared observability stack, with alerting and rollback.

  • Build the pipeline for packaging and delivering models to mobile and wearable devices, in partnership with the on-device AI/ML engineer.

  • Support deployment and monitoring of LLM and agentic services, including prompt and model versioning and evaluation runs.

  • Own training and inference cost and ML tooling decisions; partner with DevOps and SRE on infrastructure capacity, scalability, and reliability.

  • Ensure the ML platform meets security, privacy, and compliance requirements (HIPAA, GDPR) and produces audit-ready records.

  • undefined

Qualifications:

  • Bachelor’s degree in Engineering, Mathematics, Computer Science, or a related field.

  • Minimum 8 years of software or ML engineering experience, including 3+ years deploying ML models on mobile or embedded devices.

  • Hands-on experience with Azure ML SDK, Azure Data Factory, Databricks and ML tooling such as MLflow, Kubeflow.

  • Strong proficiency in Python, working knowledge of containers (Docker, Kubernetes), infrastructure as code, and at least one major cloud platform.

  • Experience partnering with DevOps and SRE teams on shared infrastructure.

  • Experience with data lakes, streaming or time-series data, and feature stores.

  • Proven experience implementing model monitoring, drift detection, and automated retraining.

Preferred Qualifications

  • Ph.D. or master’s degree in computer science, Machine Learning or a related field.

  • Experience in a regulated industry, ideally medical devices or SaMD, including validated software environments.

  • Familiarity with IEC 62304, ISO 13485, FDA guidance on AI/ML-enabled devices, and HIPAA.

  • Experience deploying models to mobile or edge devices.

  • Experience supporting LLM operations, such as prompt management, evaluation pipelines, and inference cost control.

  • Experience with high-volume IoT or wearable sensor data.

  • undefined

Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com (http://www.abbottbenefits.com/pages/candidate.aspx)

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.

Connect with us at www.abbott.com , on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal

#software

The base pay for this position is $114,000.00 – $228,000.00. In specific locations, the pay range may vary from the range posted.

An Equal Opportunity Employer

Abbot welcomes and encourages diversity in our workforce.

We provide reasonable accommodation to qualified individuals with disabilities.

To request accommodation, please call 224-667-4913 or email [email protected]

How this job compares

Set against the 6,240 open Machine Learning Engineer jobs on Olive Jobs, counted November 12, 2026.

Pay
  • This posting$114–228K/yr
  • California median$176–261K/yr1,409 salary ranges
  • US median$145–245K/yr5,195 salary ranges

This range's midpoint, $171K, is 22% below the California median midpoint ($220K) — in the lowest quarter of Machine Learning Engineer salary ranges in California.

Openings
Olive Jobs lists 1,831 open Machine Learning Engineer jobs in California and 6,240 across the US. 7% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 8 years of experience — more than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 5,158 postings).
Education
This posting asks for a bachelor's degree; 2,118 of the 6,240 open Machine Learning Engineer jobs (34%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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