Machine Learning Engineer at Research Square
As a Machine Learning Engineer, you will play a key role in developing and supporting our suite of AI digital products and service delivery capabilities.
Academic and Professional Qualifications
- Bachelor’s degree in related field or equivalent related experience
- Minimum 2 to 5 years of professional experience as a Machine Learning Engineer
- Experience with Python, relational and unstructured datasets, MySQL, version control (Git)
- Python’s ML ecosystem (NumPy or panda, etc.).
- Optimizing existing or new ML solutions for performance and scale
- Experience with natural language processing or a strong desire to learn
- Demonstrated experience with deep learning
- Natural Language Processing and/or Computational linguistics
- Amazon Web Services and/or Google Cloud
- Domain-Driven Design and Test-Driven Design
- Working Arrangements
- Relocation is not required as this position can be remote based.
About Research Square
Research Square Company, a five-time INC 5000 award winner, exists to make research communication faster, fairer, and more useful. Through our industry leading preprint platform, Research Square, research promotion tools, and AJE’s comprehensive suite of manuscript preparation services, we are proud to have supported over 2.5 million authors in 192 countries since our founding in 2004. Across all sides of our business, our team of former researchers and publishing industry professionals truly understand the importance of sharing research results with the world. By helping researchers communicate their work more effectively, we accelerate the pace of global discovery and advancement.
What we will expect from you once you’re here
As a Machine Learning Engineer, you will 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.
Experience you will need
- 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
- 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
- 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