Senior AI/ML Engineer

Abbott

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Alameda, CA
Salary: $114,000–$228,000 / yr
Employment: Full-time
Posted: 12 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $210k

This role $171k

$97k $273k

below market most similar roles pay here above market

This role pays less than 75% of similar roles. Most pay $173,050–$246,150 — the blue band above. At the midpoint, this role pays about $171k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Abbott

Abbott Laboratories is a global healthcare company that manufactures and markets a broad and diversified line of health care products including diagnostics, medical devices, nutritionals, and branded generic pharmaceuticals. Industry: Healthcare & Medical Devices

Abbott currently has 193 open roles on FindRole.

Listed pay typically runs $99,300–$198,700 across 123 roles with salary data.

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View all roles at Abbott

At a glance

TL;DR · Senior AI/ML Engineer

Role Posting Log in to save

The Senior AI/ML Engineer joins the Lingo team to bridge the gap between research and product by turning data science models into production services. You will productionize time-series and personalization models for glucose insights, refactor code for reliability, and build batch and real-time inference services with specific latency and cost targets. Key responsibilities include building feature pipelines using sensor, meal, and activity data while handling real-world sensor challenges like noise and calibration drift. You will utilize Python, PyTorch, TensorFlow, or scikit-learn alongside cloud platforms, containers, and ML pipelines. The role requires expertise in time-series modeling, CI/CD, and version control to solve technical problems within a health platform that processes millions of daily sensor readings for continuous biosensor data and personalized health insights.

Skills

Python PyTorch TensorFlow scikit-learn CI/CD Kafka Azure Event Hubs Kinesis Spark Streaming Time-series Modeling Anomaly Detection Version Control Feature Pipelines

What you'll do

Productionize time-series and personalization models into scalable, monitored cloud services.
Refactor and optimize data science code for performance, reliability, and maintainability.
Build batch and real-time inference services with specific latency, cost, and availability targets.
Expose model outputs as reliable tools and signals for the agentic AI team.
Build and maintain feature pipelines using sensor, meal, activity, and user context data.
Address real-world sensor challenges including missing data, noise, and calibration drift.
Contribute to design reviews, verification activities, and technical documentation for regulatory compliance.

What we're looking for

Bachelor’s degree in computer science or a related field.
Minimum 8 years of software or ML engineering experience.
Minimum 3 years of experience deploying ML models to production.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
Experience with time-series modeling or forecasting in production.
Experience with cloud platforms, containers, and ML pipelines.
Solid software engineering practices including testing, code review, CI/CD, and version control.
Master’s degree in computer science, Machine Learning, or a related field (preferred).

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