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Job Description: AI/ML Apprentice (Embedded Systems) – Infusion Systems Group

Role Summary

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.

Key Responsibilities

Embedded + AI Integration

• Assist in developing AI/ML-based algorithms for infusion safety (e.g., anomaly detection, flow deviation, occlusion detection)
• Support integration of ML models into embedded firmware / edge devices
• Work with real-time sensor data (pressure, ultrasonic, flow sensors) for pattern recognition and inference

Data Processing & Feature Engineering

• Analyze high-frequency device data (infusion logs, alarms, sensor signals)
• Perform preprocessing, filtering, and feature extraction for ML pipelines
• Assist in developing signal-processing pipelines for real-time inference

Model Development & Validation

• Build and evaluate basic ML models (classification/regression/clustering)
• Support model tuning, validation, and performance analysis
• Collaborate in testing model behavior across normal and fault conditions (under/over infusion, occlusions, misloads)

System & Platform Exposure

• Work on embedded platforms involving: Microcontrollers / RTOS basics Data acquisition from sensors Edge-to-cloud data pipelines
• Contribute to prototype implementations and PoC development

Quality & Compliance Awareness

• Follow software development practices aligned with medical device standards
• Support documentation, traceability, and test artifacts generation

Learning Outcomes (Apprenticeship Goals)

• Exposure to AI/ML in regulated medical devices (SaMD concepts)
• Hands-on experience with embedded + AI co-design
• Understanding of real-time safety-critical systems
• Exposure to end-to-end product lifecycle (design → validation → deployment)

Required Qualifications

• Bachelor’s degree (or final year) in: Computer Science / Electronics / Electrical / Biomedical Engineering
• Academic exposure to: Machine Learning / AI fundamentals Embedded systems or microcontrollers

Technical Skills (Preferred)

• Programming: Python, C/C++
• Basic understanding of: Data structures and algorithms Signal processing fundamentals Embedded systems concepts (RTOS, drivers – basic level)
• 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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