Senior Machine Learning Engineer for Research Team

GR8 Tech

Подробности
Основная информация
Компания

What you’ll drive:

Technical Leadership & Ownership

Take technical ownership of core components of recommendation and personalization systems (retrieval, ranking, evaluation).
Design and evolve two-tower / embedding-based retrieval models and downstream rankers.
Drive architectural and modeling decisions with a strong understanding of trade-offs between model quality, system complexity, latency, and cost.
Define and promote best practices for ML system design, experimentation, evaluation, and deployment.
Review ML designs, pipelines, and code with a focus on correctness, maintainability, and production readiness.
Act as a technical point of reference for ML-related decisions within the team

Hands-on ML Development

Develop, train, and improve ML models for retrieval and ranking use cases.
Work with embedding-based deep learning models and classical ML approaches.
Perform in-depth data analysis, feature exploration, and systematic error analysis.
Build reproducible experiments and robust offline evaluation pipelines.
Optimize models for both offline metrics and online business KPIs.
Design and operate batch and real-time training and inference workflows in a cloud environment, with awareness of scalability and cost trade-offs.

Experimentation & Production

Design, run, and analyze offline experiments and online A/B tests.
Own ML components in production, with a strong focus on reliability, observability, and safe iteration.
Monitor model performance and data quality in production.
Collaborate on scalable training and serving infrastructure for ML systems.
Participate in incident analysis related to ML systems and contribute to root-cause analysis and long-term fixes.
Design ML systems with failure modes in mind, including fallbacks and graceful degradation.

Collaboration & Mentorship

Work closely with Data Engineering on data pipelines and feature generation.
Partner with Product and Analytics to translate business goals into clear ML objectives and success metrics.
Act as a technical mentor for ML engineers, providing guidance on modeling, experimentation, and production ML.
Provide constructive feedback through code reviews and design discussions, supporting the growth of the team.

What makes you a GR8 fit:

Must-have

5+ years of experience in Machine Learning / Applied Data Science.
Strong Python skills and experience writing production-quality ML code.
Solid foundation in core ML and data science tools: NumPy, Pandas, scikit-learn, etc.
Hands-on experience with deep learning frameworks (PyTorch or TensorFlow).
Practical experience with embedding models and similarity-based retrieval.
Experience with tree-based models (LightGBM, XGBoost).
Strong understanding of ML evaluation, experimentation, and applied statistics.
Experience deploying, operating, and maintaining ML models in production environments.
Proficiency with Git, Linux, Docker, and standard ML development workflows.
Practical experience deploying ML systems in a cloud environment (AWS or equivalent).

Nice-to-have

Direct experience with recommendation systems or search-related problems.
Experience designing or operating two-tower / dual-encoder architectures.
Familiarity with ANN methods and large-scale retrieval (e.g., FAISS or equivalents).
Understanding of common ML production challenges (training–serving skew, data leakage, model drift).
Experience collaborating on data pipelines and feature engineering at scale.
Experience leading or mentoring other ML engineers.
Experience with experiment automation and hyperparameter optimization (Optuna, Ray /Tune, Hyperopt, or cloud-native equivalents).
Background in high-scale consumer products (content, gaming, media, marketplaces).
Experience working with CI/CD pipelines for ML workflows (training, evaluation, deployment).

Tech Stack

Languages: Python, SQL.
Core ML / DS: NumPy, Pandas, scikit-learn.
Deep Learning: PyTorch / TensorFlow.
ML Models: LightGBM, XGBoost.
Retrieval: Embeddings, ANN.
Cloud & Data: AWS, SageMaker, S3, Glue.
Dev & MLOps: Git, Docker, Linux.

Why you’ll love working here:

Benefits Cafeteria — annual budget you allocate to:

Sports • Medical • Mental health • Home office • Languages.

Work-life & support

Paid maternity/paternity leave + monthly childcare allowance.
20+ vacation days, unlimited sick leave, emergency time off.
Remote-first + tech support + coworking compensation.
Team events (online/offline/offsite).
Learning culture with internal courses + growth programs.

Брутто-зарплата в месяцБрутто/мес. € 4000 - 6000

Дополнительная информация: 20+ vacation days, unlimited sick leave, emergency time off.

Место работы

Rīga, Латвия
Удалённая работа

Тип работы

Полный рабочий день

Контактное лицо
Yelyzaveta Merezhko

GR8 Tech is a global product company that provides innovative, scalable platforms and business solutions for the iGaming industry. We provide great gaming tech to satisfy even greater ambition. Leveraging our extensive experience, the GR8 Tech platform successfully handles millions of active players, offering cutting-edge practices for development and growth in the gambling industry. We develop complete tech coverage for gambling businesses worldwide, including iGaming platform solutions, consulting, integration, and long-lasting operation services.

Operating in the dynamic tech market, GR8 Tech is committed to providing comprehensive support and development opportunities for our employees. Remote work is one of our most valuable benefits. We believe that in todays world, it is entirely possible to work from anywhere while maintaining a healthy work-life balance. The foundation of successful remote work lies in loyalty, trust in people and support at all levels. Join us!