TL;DR
Senior MLOps Engineer (Python): Building and scaling a shared Machine Learning platform for a large-scale retail ecosystem with an accent on MLOps infrastructure, deployment pipelines, and platform reliability. Focus on designing reusable ML capabilities, optimizing production-grade workloads on Kubernetes, and enabling seamless integration across distributed systems.
Location: Must be based in Eastern Europe
Company
Zoolatech is an outsourcing company providing engineering services for high-scale products.
What you will do
- Support and contribute hands-on to multiple ML platform proof-of-concepts.
- Evaluate and implement platform capabilities including GPU training, real-time/batch inference, and orchestration.
- Analyze performance, scalability, and integration with existing large-scale systems.
- Contribute to key architectural decisions including tooling and build vs. buy strategies.
- Support early production rollout and define platform governance standards.
- Enable onboarding of product teams onto the shared ML platform.
Requirements
- Location: Must be based in Eastern Europe
- 5+ years of experience building production-grade ML or large-scale data systems on cloud platforms.
- Strong proficiency in distributed systems, specifically Docker and Kubernetes.
- Experience with stream or batch processing systems like Kafka, Spark, or Flink.
- Proven ability to design scalable, low-latency systems in production environments.
- Strong understanding of reliability, monitoring, and safe deployment practices.
Nice to have
- Experience running ML workloads on Kubernetes using GPU or multi-tenant setups.
- Familiarity with enterprise ML platforms like Databricks.
- Experience in platform-level infrastructure cost optimization and developer onboarding.
Culture & Benefits
- Paid vacation and sick leave policies.
- Floating holidays and support for charitable initiatives.
- Compensation for sports and medical insurance.
- Budget for professional training and learning opportunities.
- Company-provided English classes.
