Lead ML Engineer @

8 hours ago

Remote Warsaw, Czech Republic hubQuest Full time
  • Advanced degree in computer science, statistics, or a related STEM field.
  • At least 5 years of ML engineering (or engineering support for data science) experience in an industrial/commercial setting.
  • Deep knowledge of ML algorithms and data science concepts.
  • Experience with ML frameworks such as TensorFlow, PyTorch, and MLflow.
  • Strong Python software engineering skills, with expertise in its ML stack.
  • Experience working with large datasets using PySpark and RDBMs.
  • Knowledge of application architectures and design patterns.
  • Knowledge of automated model deployment pipelines and scalable ML architectures.
  • Proficiency in developing, deploying, and managing ML solutions in a cloud-hosted environment.
  • Experience with MLOps frameworks, including CI/CD and continuous monitoring.
  • Expertise in DevOps technologies, such as Docker and Kubernetes.
  • Proficiency in Azure cloud services and infrastructure.
  • Proficiency in Azure-based ML solutions, including Azure Machine Learning, Azure Databricks, and Azure Data Factory.
  • Experience using version control systems (e.g., Git).
  • Experience in Agile environments.
  • Ability to effectively communicate with business stakeholders to design impactful data products.
  • Professional, service-oriented attitude.
  • Fluent in English.

We are a team of experts, bringing together the best talents in IT and analytics. Our mission is to provide innovative solutions through our flagship service, which includes forming tech teams from scratch and expanding existing units, all tailored to help our partners become real data-driven entities.

Currently, we are looking for a Lead ML Engineer to support our partner in developing a Global Analytics unit - a centralized team dedicated to strengthening data-driven decision-making and creating smart data products for day-to-day operations.

About the Team

The Global Analytics team is an innovative, diverse collective of Data Scientists, Data Engineers, ML Engineers, MLOps Engineers, Business Intelligence Specialists, Software Developers, UX Designers, and more, with a presence across three continents and five countries. The team fosters collaboration, drives innovation, and ensures reliability, transforming the entire organization into a leader in data-driven decision-making.

One of the many solutions developed by the Global Analytics team is an AI-driven analytics platform—a multi-module, cutting-edge product suite that empowers sales teams with real-time insights, such as:

  • Consumer behavior change alerts to inform when key actions should be taken,
  • Route optimization for efficiency,
  • Product recommendation engines to enhance customer experience,
  • And many more advanced AI-driven solutions.

As we scale our analytics capabilities on a global level, we are looking for an experienced Lead ML Engineer to take ownership of the platform, ensuring technical excellence and effective implementation of AI-driven solutions.

What We Offer

  • High-impact projects involving Business Intelligence and IoT initiatives.
  • The opportunity to work in a global and diverse team with international reach.
  • A flexible work environment with a fully remote work option.
  • A casual atmosphere with no corporate bureaucracy.
  • A modern office in the center of Warsaw with excellent transport links.
  • Benefits such as Multisport and private medical care.
  • Vast opportunities for self-development, including online courses, knowledge exchange, and certification support.

Business Impact

The solutions developed by the Lead ML Engineer will have a direct impact on business operations, including:

  • Enhancing data-driven decision-making by providing actionable insights.
  • Improving sales performance through AI-driven product recommendations and behavioral analysis.
  • Optimizing logistics and operations via route optimization and forecasting models.
  • Driving innovation with cutting-edge ML models tailored for real-world applications.

Role Breakdown

  • 70% hands-on technical work (coding, deployment, optimization).
  • 30% leadership (team coordination, planning, reviews, stakeholder interactions).

If you are eager to work on challenging, real-world business problems, drive AI-powered, data-driven initiatives, and collaborate with top professionals worldwide, we would love to hear from you

,[Own the technical design and daily operations of the platform in collaboration with the Lead Data Scientist., Optimize and maintain ML solutions in a cloud-hosted environment (Azure)., Work with the Product Owner, Lead Data Scientist, and technical team to translate product requirements into technical tasks., Act as a technical leader, shaping the ML and MLOps strategy while coordinating the development team in alignment with sprint goals., Assist the Product Owner with sprint planning and prioritization., Oversee the creation of technical documentation., Review pull requests to ensure technical excellence., Ensure sprint tasks follow best practices (clear descriptions, acceptance criteria, etc.)., Understand business problems and design smart data products in cooperation with Data Scientists., Develop and enhance MLOps frameworks for Data Science projects, ensuring seamless integration and best practices., Architect and implement scalable Azure-based cloud infrastructure for AI-driven applications., Design and maintain automated Azure cloud pipelines to run, monitor, and retrain data science models for business applications., Support Data Engineers in streamlining data ingestion and processing workflows., Build and maintain robust deployment workflows for ML models, ensuring seamless collaboration with Data Scientists and Data Engineers., Manage the full life cycle of ML applications, including deployment, versioning, change management, monitoring, and troubleshooting., Establish and refine frameworks to measure, monitor, and optimize the quality of deployed ML solutions.] Requirements: Machine learning, Python, MLOps, Azure Tools: Agile, Scrum. Additionally: Sport subscription, Private healthcare, Training budget, Small teams, International projects, Free coffee, Bike parking, Free beverages, In-house trainings, In-house hack days, Modern office, No dress code.

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