ML Engineer — Build Scalable Models & Pipelines

GetJobSmart; Albuquerque (NM); Sur place; USD 110 000 - 170 000; Plein temps

Avantages offerts par ce poste

Health insurance

Retirement plans with employer match

Professional development opportunities

Flexible work arrangements

Résumé du poste

Vertex Prime LLC in Albuquerque, NM is seeking a Machine Learning Engineer for a full-time role. You will develop predictive models, deploy ML solutions, and collaborate with data scientists, software engineers, and product managers to align technical work with business needs.

You will design, build, and maintain ML pipelines, optimize models for performance, and stay current with AI advances. The position offers flexibility and growth within a collaborative environment.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
• 2+ years of experience in machine learning engineering.
• Strong programming skills in Python or R.

Responsabilités

• Develop and implement machine learning models to solve real-world problems.
• Collaborate with data scientists, software engineers and product managers to translate business needs into technical solutions.
• Design, build, and maintain ML pipelines and infrastructure.
• Optimize models for performance, scalability and accuracy.
• Stay up-to-date with the latest ML/AI advancements and apply them to work.

Connaissances

Python

Machine learning

R

Formation

Bachelor's degree in Computer Science, Statistics, Mathematics, or related field

Outils

TensorFlow

PyTorch

scikit-learn

Description du poste

Vertex Prime LLC in Albuquerque, NM is seeking a Machine Learning Engineer for a full-time role. You will develop predictive models, deploy ML solutions, and collaborate with data scientists, software engineers, and product managers to align technical work with business needs.

You will design, build, and maintain ML pipelines, optimize models for performance, and stay current with AI advances. The position offers flexibility and growth within a collaborative environment.