Req # 200190 Location Bengaluru, Karnataka, India Job Category Research and Development Date posted 06/10/2026

Overview : This is where new knowledge is discovered. Baxter’s Research and Development teams work cross functionally to innovate, develop and introduce creative solutions for patients needs globally. From Scientists to Engineers, your work creates the products that save and sustain lives.

- Support for Parents
- Continuing Education/ Professional Development
- Employee Heath & Well-Being Benefits
- Paid Time Off
- 2 Days a Year to Volunteer

Success Profile : What makes a successful Research and Development team member at Baxter? Take a look at some of the top traits we’re looking for and see if you’re a fit.

- Courage
- Action Oriented
- Collaborates
- Cultivates Innovation
- Manages Ambiguity
- Drives Results

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 an Senior Automation Engineer with 6+ years solid hands-on experience in AI/ML model validation and testing . This role focuses on ensuring the quality, reliability, accuracy,



and robustness of AI/ML and LLM-based systems through systematic validation, data quality checks, and automated evaluation pipelines.

Key Responsibilities : AI / ML Model Validation :

- Design and execute validation strategies for AI/ML models , including supervised learning models and large language models (LLMs).
- Perform functional, regression, and behavioral testing of ML models across versions.
- Validate model outputs for accuracy, consistency, bias, and edge cases .
- Evaluate LLM responses for correctness, relevance, hallucinations, and safety.

Data Quality, Drift & Monitoring :

- Design and implement data quality validation checks for training, validation, and inference datasets.
- Detect and analyze data drift and concept drift across model iterations and production data.
- Validate input data assumptions, feature distributions, and schema consistency.
- Collaborate with data and ML engineers to identify and resolve data-related issues impacting model performance.

Python-Based Validation & Automation :

- Develop Python-based validation scripts and frameworks to automate:

- Model evaluation

- Data validation

- Regression testing across model versions

- Implement automated checks for model performance metrics (precision, recall, F1, accuracy, etc.).

- Build reusable validation utilities that integrate with ML workflows and pipelines.





LLM & Advanced AI Testing :

- Execute LLM evaluation workflows , including:

- Prompt‑response validation

- Golden dataset comparisons

- Regression testing across prompt or model changes

- Contribute to evaluation strategies for RAG (Retrieval-Augmented Generation) or multi‑step LLM pipelines.

- Support responsible AI initiatives by testing bias, robustness, and failure modes.

Collaboration & Quality Ownership :

- Work closely with ML engineers, data scientists, platforms, and product teams .
- Actively participate in requirement discussions and model review sessions.
- Clearly document test results, risks, and quality insights for stakeholders.
- Contribute to continuous improvement of AI testing practices and standards .

Required Skills & Qualifications :

- 4+ years of hands-on experience in AI/ML model testing, validation, or quality engineering .
- Strong proficiency in Python for model validation and data analysis.
- Experience validating supervised ML models and/or LLM-based systems .
- Solid understanding of ML evaluation metrics and validation techniques.
- Experience with data quality checks, drift detection, and dataset validation .
- Familiarity with ML pipelines and model lifecycle (training, validation, inference).
- Ability to analyze model behavior and explain quality risks clearly.
- Good communication and collaboration skills.

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

📌 Sr Eng, Test (Bengaluru)
🏢 BAXTER
📍 Bengaluru