This is where your work makes a difference.
At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond.
Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results.
Here, you will find more than just a job—you will find purpose and pride.
We are seeking a highly motivated AI/ML Apprentice (Fresher) to join our Infusion Systems R&D team, working at the intersection of embedded systems, sensor data processing, and machine learning.
The role will focus on building intelligent features for infusion platforms, including real-time anomaly detection, flow rate analysis, and safety signal processing, contributing to next-generation infusion safety solutions.
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Assist in developing AI/ML-based algorithms for infusion safety (e.g., anomaly detection, flow deviation, occlusion detection)
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Support integration of ML models into embedded firmware / edge devices
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Work with real-time sensor data (pressure, ultrasonic, flow sensors) for pattern recognition and inference
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Analyze high-frequency device data (infusion logs, alarms, sensor signals)
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Perform preprocessing, filtering, and feature extraction for ML pipelines
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Assist in developing signal-processing pipelines for real-time inference
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Build and evaluate basic ML models (classification/regression/clustering)
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Support model tuning, validation, and performance analysis
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Collaborate in testing model behavior across normal and fault conditions (under/over infusion, occlusions, misloads)
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Work on embedded platforms involving: Microcontrollers / RTOS basics Data acquisition from sensors Edge-to-cloud data pipelines
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Contribute to prototype implementations and PoC development
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Follow software development practices aligned with medical device standards
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Support documentation, traceability, and test artifacts generation
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Exposure to AI/ML in regulated medical devices (SaMD concepts)
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Hands-on experience with embedded + AI co-design
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Understanding of real-time safety-critical systems
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Exposure to end-to-end product lifecycle (design validation deployment)
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Bachelor’s degree (or final year) in: Computer Science / Electronics / Electrical / Biomedical Engineering
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Academic exposure to: Machine Learning / AI fundamentals Embedded systems or microcontrollers
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Programming: Python, C/C++
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Basic understanding of: Data structures and algorithms Signal processing fundamentals Embedded systems concepts (RTOS, drivers – basic level)
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Exposure to: ML libraries (Scikit-learn, TensorFlow/PyTorch) Data handling and visualization tools
Equal Employment Opportunity
Baxter is an equal opportunity employer. Baxter evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.
Reasonable Accommodations
Baxter is committed to working with and providing reasonable accommodations to individuals with disabilities globally. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application or interview process, please click on the link here and let us know the nature of your request along with your contact information.
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