Position: Machine Learning Engineer (NLP)
Company: Data Science UA
Category: Data Science
Experience required: 3y
English level: upper

The main features this company developers included to SourceScrub over the course of the project:
- Comprehensive searching functionality tailored specifically for the needs of investors and sales representatives;
- Companies lists accumulated from all major trade shows, conferences, awards publications, buyer’s guides;
- On demand companies researches, ability to scrub particular lists;
- Companies’ profiles with in-depth and up-to-date descriptions;
- Easy integration and synchronization with SalesForce.

Requirements:
- At least 3 years in professional environment developing data science and machine learning code - deployed into production;
- Experience with python core data science libraries as well as deep learning frameworks – Keras, TensorFlow;
- Understanding of execution and deployment methods - submitting jobs to clusters, provisioning clusters in cloud hosted spark environments (Databricks), understanding of need for GPU processing and deploying to memory or compute-intensive clusters where appropriate;
- Natural Language Processing / Understanding (NLP/NLU) experience is preferred;
- Knowledge of core language processing techniques – n-gram tokenization, document term matrixes, term frequency, stemming, lemmatization, sentiment analysis and topic modeling;
- Understanding of language classification and clustering patterns – and ability to implement patterns as deployable code with some independence;
- Experience with data prep, tuning and optimizing NLP models. Knowledge of techniques to mitigate challenges of NLP classification;

Key skills: production deployments, Python, PySpark, Databricks, Spark SQL, model validation, NLP/NLU, classification, clustering, TensorFlow, Keras. Experience with cloud-first, cloud-focused data exploration, model development and deployments.

Benefits:
- Regular performance evaluation and salary revision, attractive benefits package;
- Functional offices, centres of excellence, and mentorship from competence leads to support the professional growth;
- Tech talks, open talks, and conferences; training and certifications;
- Free English courses of all levels with attentive and friendly teachers;
- Health insurance; maternity aid; corporate sports teams, hobby clubs, in-house gym or gym discounts;
- Referral program, bonuses for marriage and childbirth.