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 ML engineer will be to develop classification and prediction models, assist with the development of data pipelines for specialty instrument data, and experiment with new data and algorithmic features to maximize the efficiency and efficacy of the results. 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.
Responsibilities:
Responsibilities:
* Experiment with various statistical and machine learning models, explore new data features, generate metrics, evaluate results.
* Maintain codebase: use Object-oriented Programming and/or Functional Programming best practices, write unit tests, etc.
* Work with subject matter experts (SMEs) to evaluate models, and present results to stakeholders, demonstrating the value of the ML techniques in a manner understandable to non-data scientists.
* Help with building out and maintaining the AWS data pipeline.
As a team member you will:
* Participate in all team meetings and ceremonies in direct collaboration with other sites, provide input and feedback, take ownership on identified improvements
* Actively participate in learning and sharing activities either during informal or formal training and demos
* Demonstrate continuous technical improvement
Qualifications:
Required Qualifications:
* Master's in computer science, data science or related field and at least 2 years' relevant work experience, or equivalent. Position level commensurate with experience.
* Experience in model development using Python for machine learning, statistical, and/or mechanistic models.
* Robust programming skills in Python (e.g., numpy, pandas, scipy, scikit-learn).
* Comfortable with Git version control, as well as BASH or command prompt.
* Comfortable discovering and driving new capabilities, solutions, modeling techniques, and modeling best practices from papers, text books, and other technical documentation.
* Able to communicate results using meaningful metrics and visualizations to managers and stakeholders and receive feedback.
* You are fluent in English - speaking, reading, writing - Advanced Level
Desired (considered a plus) Qualifications:
* Experience with one or more of:
* Predictive maintenance or other time series classification and prediction applications
* Knowledge bases and semantic reasoning
* Probabilistic programming and Bayesian inference
* Big data analytics and pipelines
* Proficiency with AWS Lambda, S3, EC2, Redshift, etc.
* Experience with containerizing models and deploying them to AWS.
* Knowledge of an object-oriented or functional programming language, such as Java, C#, Scala.
In return;
This is a hybrid role and you will receive competitive compensation, great benefits and continuous professional development.
We're actively building diverse teams and welcome applications from everyone. But simply having a diverse workforce is not enough. We aim to build an inclusive environment, where everyone can contribute their best work and develop to their full potential. We celebrate our differences and recognise the importance of teams reflecting the communities they serve.
We can make reasonable adjustments to our interview process according to your needs.
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