TL;DR

Senior ML Engineer (AI): Building and optimizing reliable, production-ready ML systems with an accent on the end-to-end lifecycle from integration to deployment, monitoring, and continuous improvement. Focus on leading the design of complex ML systems, transforming business goals into data science problems, and ensuring stable, measurable value in real-world conditions.

Location: Hybrid work mode in Kazakhstan. A relocation package is offered for candidates from other regions to Kazakhstan.

Company

%hirify_global% is a team of Machine Learning Engineers focused on turning ideas and prototypes into reliable, production-ready systems, owning the end-to-end lifecycle of ML solutions.

What you will do

Take ownership of the end-to-end machine learning delivery cycle, including building, testing, deploying, and supporting solutions.
Lead the design of complex ML systems from scratch, considering architectural aspects and user needs.
Transform business goals into data science problems and define relevant metrics.
Create and maintain DS-powered services in a production environment, collaborating with other teams.
Drive automation, track performance, and mentor junior team members.
Communicate complex technical messages to diverse audiences and drive continuous improvement.

Requirements

Comprehensive experience in implementing and leading ML projects autonomously.
Expert-level proficiency in classic machine learning, deep learning, and advanced mathematics.
Strong practical knowledge of MLOps instruments for managing the ML model lifecycle.
Solid software system design skills to contribute to overall architecture, and the ability to design ML systems from scratch.
In-depth experience with event systems and deployment environments, and the ability to maintain services in production.
Proficiency in Python and its frameworks for streaming, batch, and async data processing.

Culture & Benefits

Stable salary and official employment.
Health insurance and access to professional counseling services.
Hybrid work mode and flexible schedule.
Relocation package offered for candidates from other regions.
Discount club membership and diverse internal training programs.
Partially or fully paid additional training courses and all necessary work equipment.