Research Square is the leader in ethical author-oriented solutions in the world of academic publishing. We are home to American Journal Experts (AJE), which provides solutions that help researchers communicate their work so they can get back to making discoveries.
We currently have a challenging opportunity for a bright, hardworking, and self-motivated Machine Learning Engineer. We are looking for an early-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.
As a Machine Learning Engineer at Research Square, your efforts will support our engineering and operations teams across a variety of projects involving the creation of new tools and the support and improvement of existing tools. You will be responsible for all parts of model creation from data wrangling to model testing and validation.
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
- 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
- High level of comfort with Python, SQL, 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.
- Bachelor’s degree or equivalent experience
Our ideal candidate also has experience with the following:
- One to two years experience in practical machine learning
- Optimizing existing or new ML solutions for performance and scale
- Demonstrated experience with deep learning
- Natural Language Processing and/or Computational linguistics
- Amazon Web Services and/or Google Cloud