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Aylo

MLOps Specialist

Posted 20 Days Ago
Be an Early Applicant
In-Office
Montréal, QC
Mid level
In-Office
Montréal, QC
Mid level
The MLOps Specialist will deploy, integrate, and manage generative AI models, maintain CI/CD pipelines, and ensure performance in production systems.
The summary above was generated by AI

Established in 2004, we are a tech pioneer offering world-class adult entertainment and games on some of the internet’s safest and most popular platforms. With the support of an international team of dynamic and collaborative innovators, we are on a mission to enable safe user experiences and empower our communities by celebrating diversity, inclusion, and expression — all while maintaining robust trust-and-safety protocols.

We embrace the best of both worlds! Local talent can thrive in our collaborative office space with the flexibility of a hybrid work environment, while remote team members play an integral role in shaping our dynamic culture from afar. We have offices in Montreal (Quebec), Austin (Texas) and Nicosia (Cyprus).

*A select number of positions require full-time in office attendance*

As a Generative AI Engineer, you will be at the heart of our innovation, responsible for building, integrating, and deploying cutting-edge generative AI models into our existing projects. You will act as the technical engine driving the practical application of generative AI, from experimentation and training to full-scale production deployment. The ideal candidate is a hands-on problem-solver with a strong background in DevOps or software engineering, comfortable working with new and sometimes untested Python applications on Linux, and capable of rapidly coding proofs-of-concept (PoCs) and demos.

What You'll Be Doing:

  • Model Deployment and Integration: Design, build, and maintain the infrastructure for deploying generative AI models like Stable Diffusion, FLUX, and various Large Language Models (LLMs) into production environments.
  • Hands-on Implementation: Install, configure, manage, and troubleshoot new and untested Python-based AI applications and libraries on Linux systems.
  • Rapid Prototyping: Quickly develop and code proofs-of-concept and interactive demos to showcase the potential of new AI models and features.
  • Model Customization and Training: Take the lead on training diffusion models and fine-tuning LLMs to meet specific project requirements.
  • Dataset and Asset Creation: Build and manage high-quality datasets for training and create custom LoRA (Low-Rank Adaptation) models to adapt foundation models for specialized tasks.
  • MLOps Pipeline Management: Develop and maintain CI/CD pipelines for machine learning, automating the processes of model training, evaluation, and deployment.
  • Full-Stack Development: Write and adjust code across the stack (Python, PHP, Bash, HTML, JS) to ensure seamless integration of AI models with our platforms.
  • Performance Monitoring: Collaborate with DevOps and Engineering teams to monitor model performance, troubleshoot integration issues, and ensure scalable, secure deployments using tools like vLLM for high-throughput serving.

What you’ll need to be successful:

Must Haves:

  • Bachelor’s degree in Computer Science/Engineering, IT, or a related field.
  • 3-5 years of experience in a DevOps, MLOps, or Backend Engineering role.
  • Expert-level knowledge of Python and standard ML frameworks (e.g., PyTorch, TensorFlow).
  • Strong proficiency in PHP, Bash, HTML, and JavaScript for full-stack integration.
  • Extensive, hands-on experience with Linux environments and command-line operations.
  • Proven experience deploying and managing generative AI models, specifically Stable Diffusion, FLUX models, and various LLMs.
  • Demonstrated experience with the entire model customization lifecycle: building datasets, training diffusion models, and fine-tuning LLMs.
  • Practical experience creating and applying LoRA for model adaptation and using serving frameworks like vLLM.
  • A love for making things efficient, reliable, and a proactive mindset to take initiative.

Nice To Haves:

  • Experience with containerization and orchestration tools like Docker and Kubernetes.
  • Familiarity with building and managing CI/CD pipelines and using infrastructure-as-code tools (e.g., Terraform).
  • Industry Certifications (e.g., AWS, GCP, Azure, CKA/CKAD).
  • Professional context switcher who can adeptly move between different projects and technologies.

As an equal opportunity employer, we celebrate diversity and are committed to creating an inclusive environment for all employees

In this role you may be exposed to adult content

Top Skills

Bash
Docker
HTML
JavaScript
Kubernetes
Linux
Lora
PHP
Python
PyTorch
TensorFlow
Terraform
Vllm

Aylo Montréal, Québec, CAN Office

Montréal, Quebec, Canada

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