Engineering

Machine Learning Engineer (MLOps)

Remote
Work Type: Full Time
Ambush is a people first company where talented, thoughtful individuals come together to build meaningful products and lasting partnerships. We believe the best work happens when people feel supported, trusted and empowered to bring their full abilities to the table.
Since 2015, because of our people first and long term mindset, we have grown into a partner relied on by some of the best companies in the world. We combine strong engineering, design and strategy with a growing strength in AI to help our clients see what is next and achieve bigger outcomes.
At the heart of everything we do is our team. We collaborate, take risks, lift each other up and take pride in doing work the right way, not settling for a quick makeshift solution. If you join Ambush, you join a group of people who want you to succeed and who show up for each other every day.
We believe in and expect real teamwork, a constant drive to be better, and delivering meaningful long term outcomes that we can be proud of together.

Key Responsibilities

End-to-End AI Implementation: Drive the lifecycle of Generative AI solutions to meet evolving business needs.

Reliable Delivery Systems: Unify classification models and backend services under a single, robust CI/CD framework.

Infrastructure Empowerment: Mentor infrastructure staff on modern IaC practices to ensure long-term maintainability and transparent cloud governance.

MLOps Excellence: Streamline the transition of models from research to production through collaborative monitoring and pipeline integration.


Required Experience & Skills

Advanced MLOps & CI/CD Engineering: Proven expertise in architecting end-to-end MLOps workflows and robust CI/CD pipelines. You should have a track record of automating the seamless deployment of high-performance machine learning models alongside mission-critical backend web services.

Azure Cloud Mastery: Extensive hands-on experience as an Azure subject matter expert. You are proficient in leveraging the full Azure ecosystem (e.g., AKS, Azure ML, App Service) to design resilient, secure, and scalable hosting environments for global production traffic.

Generative AI & LLM Productization: Deep technical proficiency in developing and scaling Generative AI applications. You have experience transforming Large Language Models (LLMs) from experimental notebooks into production-ready solutions optimized for complex text generation and processing.

Infrastructure as Code (IaC) Leadership: A strict "IaC-first" mentality with mastery of tools such as Terraform. You are committed to infrastructure transparency, repeatability, and providing technical mentorship to cross-functional teams.

Agile Technical Decision-Making: Experience thriving in Agile environments. You possess the communication skills and technical confidence to contribute to rapid sprint cycles and drive high-impact architectural decisions.

Experience level:
Senior-level
 

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