Machine Learning Engineer

4 Corner Resources; Orlando (FL); Hybrid; USD 100,000 - 120,000; Full time

Job summary

A technology consulting firm is seeking a Machine Learning Engineer to develop and deploy advanced computer vision models. The ideal candidate will have deep learning expertise and experience with Kubernetes for building scalable ML workflows. Responsibilities include optimizing CV models and tuning hyperparameters. This is a hybrid contract position located in Orlando, Florida, suitable for a mid-senior level professional.

Qualifications

• Proven experience deploying computer vision models in real-world environments.
• Strong background in deep learning frameworks.
• Hands-on experience with containerization and orchestration.

Responsibilities

• Deploy and optimize high-performance CV models for speed and accuracy.
• Build scalable training and deployment pipelines using Kubernetes.
• Conduct hyperparameter tuning and model optimization.

Skills

Deep learning frameworks (e.g., PyTorch, TensorFlow)

Containerization and orchestration (Kubernetes)

Computer vision model deployment

MLOps best practices

Job description

Overview

4 Corner Resources is searching for a Machine Learning Engineer to support the development and deployment of advanced CV models in a production environment. This role combines deep learning expertise with infrastructure engineering, contributing to scalable ML workflows that power real-world applications.

Responsibilities

• Deploy and optimize high-performance CV models (e.g., YOLO, OWL) for speed and accuracy
• Build scalable training and deployment pipelines using Kubernetes and Ubuntu-based systems
• Conduct hyperparameter tuning and model optimization to align with technical and business KPIs
• Develop reusable tools for model evaluation, monitoring, and performance tracking
• Work cross-functionally to integrate CV models into production environments and automate the ML lifecycle
• Stay informed on emerging research in computer vision and apply cutting-edge methods (e.g., foundation models, prompt-based detection)

Qualifications

• Proven experience deploying computer vision models in real-world environments
• Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow)
• Hands-on experience with containerization, orchestration (Kubernetes), and Linux-based systems
• Solid understanding of MLOps best practices and production ML pipelines
• Familiarity with modern CV techniques and the ability to translate research into practical solutions

Location

Hybrid (Onsite/Remote)

Duration

6-month contract

Seniority level

Mid-Senior level

Employment type

Contract

Job function

Information Technology

Industries

Hospitality