Research Square Company is in search of a Machine Learning Engineer to play a key role in developing and supporting our suite of AI digital products and service delivery capabilities. This person will work closely with our growing machine learning team and cross-functional stakeholders in Product and Service Delivery Operations to advance our AI initiatives. They will collaborate on all parts of AI model creation from data wrangling to testing and validation. The successful candidate will be an early- to mid-career individual who exhibits personal humility and who strives to enable the success of their team in our fun and collaborative remote environment. A successful candidate will be excited to learn and stay abreast of new advancements in the field.

Requirements for this role include

Uses appropriate ML techniques and big data to create automation solutions for business-critical problems
Assesses and advocates for automation solutions based on their cost to implement and probability of success
Considers scalability, user experience, and biases in data when designing solutions
Has experience with natural language processing or a strong desire to learn
Collaborates with business stakeholders to understand business objectives and develop models to help achieve them, along with metrics to track their effectiveness
Works both strategically and tactically to achieve business outcomes
Has a high level of comfort with Python, relational and unstructured datasets, Git, and using the command line
Works with complex structured and unstructured data, to include leading the data acquisition process, data cleaning, exploratory analysis, verification, and designing data pipelines.
Validates models to ensure adequate real-world performance
Has a Bachelor’s degree or equivalent experience

Our ideal candidate has 1-5 years experience in practical machine learning and experience with:

Optimizing existing or new ML solutions for performance and scale
Deep learning
Natural Language Processing and/or Computational linguistics
Amazon Web Services and/or Google Cloud
Domain-Driven Design and Test-Driven Design

Who We Are

Research Square Company exists to make research communication faster, fairer, and more useful. We are a growing team of scientists, researchers, language experts, software engineers, and publishing industry veterans working together to find new ways to help researchers succeed.

Headquartered in Durham, North Carolina, Research Square Company consists of two main divisions, American Journal Experts (AJE) and Research Square. Since 2004, AJE has provided manuscript preparation services to hundreds of thousands of researchers helping them to get their work published. Launched in 2018, our platform, Research Square, is the largest multidisciplinary preprint server in the world. By helping researchers communicate their work more effectively, we accelerate the pace of global discovery and advancement.

Our team embraces and fuels change, fights for simplicity, invests in customers’ success, and applies a data-driven approach to continuously improve and magnify our impact. We have developed tools and services that have been adopted by major international publishers to improve the publishing experience for their authors.

We are a high-growth, family-friendly, and mission-driven company that regularly wins awards for our workplace culture, pace of growth, and innovations. Our organization is casual and flexible while also being stimulating and dynamic. We have a results-focused work environment. Employees work remotely from anywhere in the US.

Benefits

https://company.researchsquare.com/careers/

Workplace Recognition

Sloan Award for Workplace Flexibility (2011, 2012)
When Work Works Award (2014, 2016, 2017)
NC Parenting Magazine’s Family Friendly 50 (2013, 2014)
Triangle Business Journal's Best Places to Work (2017, 2019, 2020)
NCBC Breastfeeding-Friendly Employer Award (2017)
Family Forward NC Featured Business (2019)

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For the following exercise, submit your answer or provide an external link below. Please include the code, the output, and the explanation.
Two models were trained using the following data:
x = [0, 1, 2, 3, 4]
y = [0.1, 0.9, 2.1, 2.9, 4.1]
Model 1 predicted y_1 = [0, 1, 2, 3, 4], and model 2 predicted y_2 = [0.1, 0.9, 2.1, 2.9, 4.1].
Write a Python function that computes the root mean square error (RMSE) for each model. For the test point (x, y) = (5, 5.1), model 1 predicted y_1 = 5, and model 2 predicted y_2 = 5.2. Which model is better and why?*

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Machine Learning Engineer - Digital Services (Remote, USA)

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