Research Senior Software Data / AWS Engineer

Overview

Come help us research and develop self-diagnosing, self-healing instruments!

The Waters Global Research department is exploring state-of-the-art capabilities that will stretch your creative talents. Our aim is to enhance our customers’ user experience by building more intelligent systems. Our analytical chemistry instruments have a direct impact on laboratory testing, drug discovery and development and food safety, and we strive to enhance our software offerings, making them more intuitive and easier to use.

The current work focuses on training machine learning and other statistical models that perform root error diagnosis using raw signals time series data coming from our instruments. Other projects include automating steps that users currently do manually, such as interpreting raw data results, adjusting anomalous data to clean it up, and optimizing the procedures that the instruments run on.

The role of this Data / AWS engineer will be to develop data pipelines for specialty instrument data and Gen AI processes, support the development of classification and prediction models, create and maintain dashboards to monitor data health, and set up and maintain services in AWS to deploy models, and collect results. These pipelines will be part of foundational emerging data infrastructure for the company. We seek someone with a growth mindset who is self-motivated, a problem solver, and someone energized by working at the nexus of leading-edge software and hardware development.

This position will follow a hybrid model work approach( 3 days a week , Tuesday, Wednesday and Thursday working from GCC office, RMZ ecoworld, Bellandur, Bangalore).

Responsibilities

• Build data pipelines in AWS using S3, Lambda, IoT core, EC2, and other services.
• Create and maintain dashboards to monitor data health.
• Containerize models and deploy them to AWS
• Build python data pipelines that can handle data frames and matrices, ingest, transform, and store data using pythonic code practices.
• Maintain codebase : use OOP and / or FP best practices, write unit tests, etc.
• Work with Machine Learning engineers to evaluate data and models, and present results to stakeholders in a manner understandable to non-data scientists.
• Mentor and review code of other members of the team.

Qualifications

Required Qualifications :

Desired (considered a plus) Qualifications :

What We Offer :

Company Description

Waters Corporation (NYSE : WAT), the world's leading specialty measurement company, has pioneered chromatography, mass spectrometry and thermal analysis innovations serving the life, materials, and food sciences for over 60 years. With approximately 8,000 employees worldwide, Waters operates directly in 35 countries, including 15 manufacturing facilities, with products available in more than 100 countries. Our team focuses on creating business advantages for laboratory-dependent organizations to enable significant advancement in healthcare delivery, environmental management, food safety, and water quality.

Working at Waters enables our employees to unlock the potential of their careers. Our global team is driven by purpose. We strive to be better, learn and improve every day in everything we do. We’re the problem solvers and innovators that aren’t afraid to take risks to transform the world of human health and well-being. We’re all in it together delivering benefit as one to provide the insights needed today in order to solve the challenges of tomorrow.

Diversity and inclusion are fundamental to our core values at Waters Corporation. It is our responsibility to actively implement programs and practices to drive inclusive behavior and increase diversity across the organization. We are united by diversity and thrive on it for the benefit of our employees, our products, our customers and our community. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or protected Veteran status.