This job has been archived and is no longer active.

ML Ops Engineer

WorldwideArmeniaSpainGeorgiaSerbiaRelocationRemoteSenior

Key Skills and Responsibilities

LLM Serving & Model Management:

Deep expertise in high-throughput serving using vLLM, NVIDIA TensorRT-LLM, and sglang to minimize latency and maximize hardware efficiency.
Hands-on experience deploying and optimizing large-scale open-weights models, specifically DeepSeek 3.1/3.2, Qwen, and GPT-OSS variants.
Advanced optimization and security hardening of Docker specifically for GPU environments.
Managing model weights and orchestration within Kubernetes (GKE) environments.
Real-Time Data Engineering & CDC:
Designing and maintaining high-throughput CDC (Change Data Capture) pipelines using the Apache ecosystem (e.g., Debezium, Kafka) to sync data from Cloud PostgreSQL.
Deploying and tuning ClickHouse for real-time analytics, ML feature storage, and high-speed logging.
Orchestrating complex ML data workflows using Airflow (Google Cloud Composer) to ensure data reliability. Must

Core Infrastructure & Networking:

Strong Linux systems expertise including internals, networking, and performance tuning for large-scale distributed systems.
Experience with Istio service mesh to manage microservices communication and traffic.
Provisioning and maintaining dedicated GPU nodes (A100/H100/H200/B200), including driver management and OS-level tuning using Ansible.
Solid Kubernetes expertise: controllers, CRDs, CNI, and Ingress.
CI/CD & Tooling:
Implementing pipelines as code within GitLab CI, managing runners, caching, and security scanning.
Infrastructure as Code with Terraform and Terragrunt.
Proficiency in Python/Bash for building custom automation and AI Agent tooling.

Load Testing & Observability:

Conducting rigorous load testing for GenAI applications, focusing on metrics like TTFT, TPS, and RPS.
Deploying and managing LiteLLM Gateway for unified API access, load balancing, and cost tracking.
Experience with Datadog for monitoring GPU utilization, inference health, and log pipelines.

Soft Skills:

Strong ownership mindset: balancing speed, reliability, and cost.
Comfortable working cross-functionally with developers, security, and compliance.
Excellent sense of responsibility and accountability.
English B2 or higher.

Nice to Have:

Experience with PCI-DSS, SOC2, or regulations compliance environments.

Our Tech Stack: Linux, Docker, Kubernetes, GCP (GKE, Cloud PostgreSQL), Datadog, GitLab, Apache CDC, ClickHouse, Airflow, Istio, Terraform, Terragrunt, Ansible, vLLM, TensorRT-LLM, sglang, LiteLLM, DeepSeek, Qwen, Go, Python

What we offer

Full-time B2B contract
Fully remote setup, work from anywhere in Europe
Up to 20% tax allowance
22 paid leave days annually
Stock options (ESOP) in a fast-scaling, pre-IPO company
Flexi benefits you can use for wellness, travel, or learning
Work alongside a high-performing, international engineering team in a global fintech unicorn

Relocation support is available to our hubs in Armenia, Georgia, Serbia, and Spain, including flights, temporary accommodation, and legal setup.

Tabby

Tabby is a UAE-based buy now, pay later method that enables customers to purchase products online or in store and split the payment over 4 monthly installments.

See all 7 jobs at Tabby

Key Skills and Responsibilities

LLM Serving & Model Management:

Deep expertise in high-throughput serving using vLLM, NVIDIA TensorRT-LLM, and sglang to minimize latency and maximize hardware efficiency.

Hands-on experience deploying and optimizing large-scale open-weights models, specifically DeepSeek 3.1/3.2, Qwen, and GPT-OSS variants.

Advanced optimization and security hardening of Docker specifically for GPU environments.

Managing model weights and orchestration within Kubernetes (GKE) environments.

Real-Time Data Engineering & CDC:

Designing and maintaining high-throughput CDC (Change Data Capture) pipelines using the Apache ecosystem (e.g., Debezium, Kafka) to sync data from Cloud PostgreSQL.

Deploying and tuning ClickHouse for real-time analytics, ML feature storage, and high-speed logging.

Orchestrating complex ML data workflows using Airflow (Google Cloud Composer) to ensure data reliability. Must

Core Infrastructure & Networking:

Strong Linux systems expertise including internals, networking, and performance tuning for large-scale distributed systems.

Experience with Istio service mesh to manage microservices communication and traffic.

Provisioning and maintaining dedicated GPU nodes (A100/H100/H200/B200), including driver management and OS-level tuning using Ansible.

Solid Kubernetes expertise: controllers, CRDs, CNI, and Ingress.

CI/CD & Tooling:

Implementing pipelines as code within GitLab CI, managing runners, caching, and security scanning.

Infrastructure as Code with Terraform and Terragrunt.

Proficiency in Python/Bash for building custom automation and AI Agent tooling.

Load Testing & Observability:

Conducting rigorous load testing for GenAI applications, focusing on metrics like TTFT, TPS, and RPS.

Deploying and managing LiteLLM Gateway for unified API access, load balancing, and cost tracking.

Experience with Datadog for monitoring GPU utilization, inference health, and log pipelines.

Soft Skills:

Strong ownership mindset: balancing speed, reliability, and cost.

Comfortable working cross-functionally with developers, security, and compliance.

Excellent sense of responsibility and accountability.

English B2 or higher.

Nice to Have:

Experience with PCI-DSS, SOC2, or regulations compliance environments.

What we offer

Full-time B2B contract

Fully remote setup, work from anywhere in Europe

Up to 20% tax allowance

22 paid leave days annually

Stock options (ESOP) in a fast-scaling, pre-IPO company

Flexi benefits you can use for wellness, travel, or learning

Work alongside a high-performing, international engineering team in a global fintech unicorn

Relocation support is available to our hubs in Armenia, Georgia, Serbia, and Spain, including flights, temporary accommodation, and legal setup.