ML Engineer (AI)

TL;DR

ML Engineer (AI): Building and deploying production-ready machine learning solutions from end to end with an accent on integration, deployment, monitoring, and continuous improvement. Focus on ensuring models deliver stable, measurable value and solving engineering design and delivery issues.

Location: Hybrid work mode in Kazakhstan

Company

hirify.global is a team of Machine Learning Engineers focused on turning ideas and prototypes into reliable, production-ready systems.

What you will do

• Build and deploy machine learning solutions from end to end, contributing to the full ML delivery cycle.
• Conduct data analysis, annotation, and processing as a key part of the ML system design.
• Design solutions using common patterns and tools, and propose alternative approaches when needed.
• Ensure solutions meet design standards, 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 the engineering design and delivery process, ensuring the solution meets KPIs and non-functional requirements.
• Collaborate with team members, contribute to a community of practice, and promote the reuse of common approaches and technologies.

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 from various sources.
• A solid understanding of business value and how it connects to delivering features.
• A proactive approach to self-development and learning new skills and best practices.

Culture & Benefits

• Stable salary and 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.
• Partially or fully paid additional training courses.
• All necessary work equipment.