Position: NLP Engineer
Company: Data-Science
Experience required: 3y
English level: upper

**Responsibilities and Requirements**
They expect Machine Learning Scientists to be versatile and have a well balanced set of skills. You will focus on model training, with significant capacity for research (developing novel model architectures), dataset construction, and model hardening (preparing the model and code for production pipelines).

**Day-to-day, your responsibilities are to:**

-Work with domain experts and product owners to determine what questions should be asked and what questions can be answered.
-Read research papers, understand requisite math, experiment with new models, write up approaches and results.
-Find the right model architecture and hyperparameters, effectively debugging along the way.
-Find optimal hyperparameters and expand dataset/build heuristics until edge cases are handled correctly.
-Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
-Write clean, efficient, and modular code, with automated tests and appropriate documentation.
-Stay up to date with technology, make good technological choices, and be able to explain them to the organization.

**Required Qualifications**

-Experience working with text data to build predictive models, both supervised and unsupervised.
-A strong understanding of the math and statistics behind machine learning theory and fluency with general machine learning domains such as classification, regression, unsupervised clustering and recommender engines.
-Software engineering background with 2-3 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
-Strong machine learning development skills (we use sklearn, keras, tensorflow, pytorch, jupyter).
-Bachelor’s or Master's degree in Computer Science, Statistics, Applied Mathematics or related field, with relevant industry experience, or outstanding previous achievements in this role.
-Good communication and teamwork skills.
-Good written and spoken English.

**Would be a plus**

-Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries
-Familiarity in front-end frameworks (e.g. React, Javascript, Flask) to build simple demos, POCs and prototypes
-Experience working with image data to build predictive models.