TL;DR

Middle ML Engineer (AI): Building and deploying end-to-end machine learning solutions, turning prototypes into reliable, production-ready systems with an accent on integration, deployment, monitoring, and continuous improvement. Focus on designing reusable and flexible solutions, ensuring they meet design standards, and delivering stable, measurable value in real-world conditions.

Location: Hybrid in Cyprus, Georgia, or Kazakhstan. Relocation package offered for candidates from other regions.

What you will do

Build and deploy end-to-end machine learning solutions, contributing to the full ML delivery cycle.
Conduct data analysis, annotation, and processing for ML system design.
Design solutions using common patterns and tools, and propose alternative approaches.
Ensure solutions meet design standards and are reusable, flexible, and extensible through peer reviews.
Deploy features, ensure they work as intended, and prevent unintended side effects.
Document technical solutions and ensure all necessary monitoring and support tools are in place.
Solve issues in engineering design and delivery, ensuring solutions meet KPIs and non-functional requirements.
Collaborate with team members, contribute to a community of practice, and promote common approaches.

Requirements

Proficiency in Python and its frameworks for streaming, batch, and asynchronous data processing.
Solid experience with classic machine learning techniques and algorithms.
Experience using MLOps tools and practices to manage the ML model lifecycle.
Familiarity with technologies like Golang for backend system and infrastructure integration.
Ability to conduct thorough data analysis and preparation.
Strong problem-solving skills with a focus on engineering principles and data-driven reasoning.
Excellent communication and collaboration skills, with an ability to seek and validate information.
A solid understanding of business value and its connection to delivering features.
A proactive approach to self-development and learning new skills and best practices.

Culture & Benefits

Stable salary, official employment.
Health insurance.
Hybrid work mode and flexible schedule.
Access to professional counseling services including psychological, financial, and legal support.
Discount club membership.
Diverse internal training programs and partially or fully paid additional training courses.
All necessary work equipment.