InData Labs is a data science firm and AI-powered solutions provider with its own R&D center. Our main focus lies in machine learning and deep learning solutions, as well as building high-load data processing systems.
Currently, we are looking for a Senior Machine Learning Engineer who will be a part of the general-purpose data science team with a focus on recommender systems for natural language content.
In this position, you will often communicate with a customer and consult both technical and non-technical team members regarding questions within your domain of machine learning and data-driven solutions.
- Understand business needs and restrictions and offer appropriate technical solutions in the domain of data-driven applications, describe qualities and limitations of proposed approaches to non-technical people.
- Work mainly with numerical and textual data, state data collection and labelling requirements and recommendations.
- Design and implement rule-based and machine learning solutions, including data preparation; selection, training, validation and optimization of machine learning models; realistic data-grounded evaluation of created solutions.
- Integrate data preprocessing, model training and inference into general data processing pipelines.
- Research new tools, papers, etc. in the machine learning area.
- Strong knowledge and deep understanding of
- Main concepts and stages of the modelling process (validation scheme, regularization, overfitting and generalization, data leaks, feature selection, etc.)
- Сlassical machine learning (linear models, decision trees, ensembles for classification and regression tasks, clustering and dimensionality reduction)
- Recommender systems fundamentals (content-based, collaborative filtering, hybrid, evaluation process)
- Understanding main problems and concepts of modern Natural Language Processing
- Hands-on experience with Python scientific and ML-related libraries (scipy, numpy, pandas, scikit-learn, xgboost/lightgbm/catboost, matplotlib/seaborn, PyTorch/TensorFlow, etc.)
- Good Python programming skills and ability to write code not only in Jupyter Notebooks
- Basic knowledge and skills of algorithms and data structures, relational databases and SQL
- Ability and desire to convert raw business requests into strictly formulated machine learning tasks, data gathering (data labelling, if needed) requirements
- At least 3-year experience in machine learning or data-driven applications development
- Good spoken and written English (at least B2)
Would be a plus:
- Experience with Linux-based operating systems, Git and Docker
- Production experience in developing recommender systems
- Experience in software engineering, deployment and integration with data delivery systems and other components, building microservices, providing APIs for models access, web scraping
- Experience with ML stack of Microsoft Azure, AWS or Google Cloud
- Data visualization and presentation skills
- Experience in Deep Learning with applications to any data domain
- Experience in data labelling process setup using third-party or self-made labelling tools
- Participation in ML competitions (Kaggle, etc), contribution to ML-related public projects
- Masters, PhD, or equivalent experience in Mathematics, Computer Science or Computational Linguistics.
What we offer:
- Competitive compensation;
- Flexible schedules available;
- Generous benefits package from day one of employment: medical coverage, sport reimbursement, English classes, bonuses for special occasions (birthday, wedding, etc.), paid vacations and sick leaves;
- Immense training and growth opportunities.
Join our team of world-class data scientists and data engineers, and challenge yourself with some of the most pressing data science and engineering tasks of modern times!