Machine Learning Engineer — Production AI Solutions

Noctua Technology; United States; On-site; USD 95,000 - 185,000; Full time

Job summary

Noctua Technology LLC is seeking a talented Machine Learning Engineer to design, develop, and deploy cutting-edge ML solutions for diverse clients. You will work on data collection, model training, evaluation, and deployment, collaborating with engineers and domain experts to deliver impact-driven AI applications.

The role emphasizes staying current with ML advances, driving innovation, and delivering maintainable code and well-documented models in a team-oriented environment.

Qualifications

• Solid understanding of machine learning concepts, algorithms, and frameworks (TensorFlow, PyTorch).
• Experience deploying machine learning models into production systems.
• Experience with containerization and orchestration tools (Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, GCP).
• Strong programming skills in Python or C++.
• Strong software engineering practices with clean, modular code and version control (Git).
• Excellent problem-solving and collaborative communication skills.

Responsibilities

• Acquire, clean, and preprocess diverse datasets from various sources.
• Develop data pipelines to ensure high-quality data flow.
• Design and implement machine learning models to solve business problems.
• Train models, conduct experiments, and optimize algorithms for performance and accuracy.
• Collaborate with software engineers, domain experts, and analysts to deliver integrated solutions.
• Create and maintain documentation for code, algorithms, and models.

Skills

TensorFlow

PyTorch

Python

C++

Git

ML algorithms

Data preprocessing

Model deployment

Tools

Docker

Kubernetes

AWS

Azure

GCP

CI/CD

Job description

Noctua Technology LLC is seeking a talented Machine Learning Engineer to design, develop, and deploy cutting-edge ML solutions for diverse clients. You will work on data collection, model training, evaluation, and deployment, collaborating with engineers and domain experts to deliver impact-driven AI applications.

The role emphasizes staying current with ML advances, driving innovation, and delivering maintainable code and well-documented models in a team-oriented environment.