Top Machine Learning Jobs in Albuquerque, NM

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.

The role involves preparing traffic data, developing and deploying machine learning models on Google Vertex AI, and collaborating with teams to improve project workflows.

The Expert Product Architect AI/ML will design technical foundations for Managed AI Services, ensuring scalable and secure integrations of AI capabilities and operational frameworks within Ensono's offerings.

Lead the Data Platform & ML Ops team, overseeing data infrastructure and ML lifecycles, mentoring engineers, and driving product innovations.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Staff ML Platform Engineer will enhance Afresh's ML platform performance and scalability, collaborating with ML teams to improve systems and deploy models efficiently.

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

The Staff Software Engineer will build and scale machine learning systems for personalization, collaborating with teams to enhance project quality and performance.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.