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

We are looking for a qualified Engineer to join the team, working on the creation of a platform for research and information management.

For M&A business development, the project provides research and information management systems that incorporate thousands of online sources from trade show exhibitor lists to industry buyers’ guides. It is working 24/7 to ensure accurate and current data for prospecting investment opportunities. The project’s sourcing data and prospecting tools promise to save time and increase deal flow. The project includes a full scope of NLP tasks starting from EDA, data preprocessing, creating machine learning models and model deployment.

**Requirements:**
- At least 3 years in professional environment developing data science and machine learning.
- Experience with python core data science libraries as well as deep learning frameworks — Keras, TensorFlow.
- Natural Language Processing / Understanding (NLP/NLU) experience. Experience with data prep, tuning and optimizing NLP models. Knowledge of techniques to mitigate challenges of NLP classification.
- 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.
- Understanding of language classification and clustering patterns and ability to implement patterns as deployable code with some independence.
- Knowledge of core language processing techniques — n-gram tokenization, document term matrixes, term frequency, stemming, lemmatization, sentiment analysis and topic modelling.
- Experience with production deployments of models in batch and real-time.

**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;
- Great team parties and corporate events; cool branded gifts; an additional paid day off for the Company Day celebration;
- Warm and relaxed atmosphere, smooth and transparent communication, and unlimited fun.