Senior AI/ML Engineer

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.

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:

• Career development with an international company where you can grow the career you dream of.
• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution.
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

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

As Senior AI/ML Engineer, you will turn models developed by our data science team, such as glucose forecasting, pattern detection, and personalization, into production services that run at scale in the cloud. You are the bridge between research and product.

You will work closely with data scientists, platform engineers, and product teams, so strong collaboration and a high level of professionalism are required. This role offers direct exposure to both data science and product engineering.

• Productionize time-series and personalization models for glucose insights, from prototype to scalable, monitored services.

• Refactor and optimize data science code for performance, reliability, and maintainability.

• Build batch and real-time inference services with defined latency, cost, and availability targets.

• Partner with the agentic AI team to expose model outputs as reliable tools and signals for agents.

• Build and maintain feature pipelines on the ML platform using sensor, meal, activity, and user context data.

• Handle real-world sensor challenges, including missing data, noise, calibration drift, and sensor warm-up periods.

• Contribute to design reviews, verification activities, and technical documentation in compliance with government and corporate regulations.

• Proactively identify problems or areas for improvement and resolve issues.

• Bachelor’s degree in computer science, or a related field.

• Minimum 8 years of software or ML engineering experience, including 3+ years 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: testing, code review, CI/CD, and version control.

• Master’s degree in computer science, Machine Learning or a related field.
  Experience in a regulated industry, ideally medical devices, digital health, or SaMD.

• Experience with physiological or wearable sensor data, such as continuous glucose monitoring.

• Familiarity with streaming technologies such as Kafka, Azure Event Hubs, Kinesis, or Spark Streaming.

• Experience with personalization, recommendation, or anomaly detection systems.

• Familiarity with HIPAA and data privacy requirements.

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