MLOps Engineer

Posted Yesterday
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2 Locations
In-Office
Senior level
Artificial Intelligence • Information Technology • Software
The Role
The MLOps Engineer will implement infrastructure and automation for scalable ML systems, ensuring compliance and efficiency in a startup environment.
Summary Generated by Built In
About Applico Capital

Applico Capital is the leading venture capital firm focused on the $8 trillion B2B distribution industry. Through our learnings and understanding of the industry, we are building a tech startup, currently in stealth, to solve the industry's biggest problems as it comes to unlocking AI-enabled synergies.

Our mandate is to leverage AI and modern technologies to reimagine the role of the traditional distributor and transform how the entire industry operates.

We are looking for highly technical builders who thrive in entrepreneurial, scrappy, and collaborative environments.

About the Role:

We are seeking an MLOps Engineer to design and implement the infrastructure, automation, and monitoring that enable machine learning to be reliable, repeatable, and scalable. You will enable our AI Scientists and Engineers to move faster, while ensuring compliance, observability, and cost efficiency.

This is a scrappy, hands-on role in a startup-style team where building durable, automated systems is as important as moving quickly. You’ll ensure that ML becomes a dependable part of daily business operations. You will also extend MLOps practices to support agentic AI systems, managing orchestration, monitoring emergent behavior, and ensuring the safe and governed use of AI-augmented workflows.

Key Responsibilities
  • Build CI/CD pipelines for ML models across training, deployment, and monitoring
  • Develop and manage feature stores, model registries, and automated retraining processes
  • Implement monitoring for model performance, data drift, and bias
  • Optimize cloud infrastructure for scalable and cost-efficient AI workloads
  • Partner with AI Engineers and Scientists to ensure fast, reproducible delivery
  • Operationalize LLM agents and multi-agent systems (e.g. containerization, scaling, observability)
  • Develop safety, governance, and monitoring frameworks for agentic AI in production

Requirements
  • 5+ years in ML engineering, DevOps, or infrastructure engineering
  • Proficiency with MLOps tools (MLflow, Kubeflow, Weights & Biases, Airflow, Dagster, Prefect)
  • Strong experience with cloud platforms and container orchestration (AWS/GCP/Azure, Docker, Kubernetes)
  • Solid understanding of ML Lifecycles and best practices for reproducibility
  • Proven ability to build scalable, automated systems in production
  • Experience deploying and monitoring agent frameworks, LLM-based APIs, or AI-augmented workflows preferred

Top Skills

Airflow
AWS
Azure
Dagster
Docker
GCP
Kubeflow
Kubernetes
Mlflow
Mlops Tools
Prefect
Weights & Biases
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The Company
HQ: Boca Raton, Florida
50 Employees
Year Founded: 2009

What We Do

We help B2B distribution's largest enterprises use technology to solve big problems and unlock new opportunities. Applico Capital brings together strategic partners and entrepreneurs to accelerate growth and create value at tremendous scale.

Through venture capital, we invest out of the B2B Distribution industry's first venture capital fund dedicated to investing in distribution tech.

Through private equity, we are the technology operating partner to large B2B Distributors as they harness AI to lead their vertical.

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