Machine Learning Engineer: Build Production AI

Noctua Technology; San Diego (CA); On-site; USD 115,000 - 185,000; Full time

Job summary

Noctua Technology, LLC is seeking a highly capable Machine Learning Engineer to design, develop, and deploy cutting-edge ML solutions for diverse client challenges. The role emphasizes building data pipelines, training and optimizing models, and collaborating with software engineers and analysts to deliver end-to-end AI systems.

The successful candidate will have strong ML fundamentals, experience with TensorFlow or PyTorch, containerization, cloud platforms, and solid software engineering

Qualifications

• Solid understanding of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch).
• Experience deploying machine learning models into production systems.
• Experience in containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience with cloud platforms (e.g., AWS, Azure, GCP).
• Strong proficiency in programming languages such as Python or C++.
• Strong software engineering skills with clean, modular, maintainable code.

Responsibilities

• Acquire, clean, and preprocess diverse datasets from various sources.
• Develop and maintain data pipelines to ensure a continuous flow of high-quality data.
• Design and implement machine learning models to solve complex business problems.
• Conduct experiments, train models, and optimize algorithms for performance and accuracy.
• Collaborate with cross-functional teams to implement integrated solutions and document code, algorithms, and models.
• Act on client feedback to improve services and continuously enhance the customer experience.
• Stay updated on the latest ML/AI developments and drive innovation within the team.

Skills

TensorFlow

PyTorch

Docker

Kubernetes

Cloud platforms

Python

C++

Git

Education

Bachelor's degree in Computer Science / AI

Tools

Spark

Hadoop

Job description

Noctua Technology, LLC is seeking a highly capable Machine Learning Engineer to design, develop, and deploy cutting-edge ML solutions for diverse client challenges. The role emphasizes building data pipelines, training and optimizing models, and collaborating with software engineers and analysts to deliver end-to-end AI systems.

The successful candidate will have strong ML fundamentals, experience with TensorFlow or PyTorch, containerization, cloud platforms, and solid software engineering