Top Machine Learning Jobs in Albuquerque, NM

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

Develop novel machine learning methods to enhance computer vision solutions, identify areas for innovation, and translate research into scalable production systems.

As a Senior Machine Learning Engineer, you'll build and upgrade recommender systems, optimize machine learning models, and improve tooling to enhance product personalization.

The Senior Principal AI/ML Architect will drive AI architectural vision, influence multi-squad strategy, design intelligent systems, and set operational standards for Yahoo Mail's AI capabilities.

The Specialist Solutions Architect will guide customers in architecting ML & AI applications, provide advanced technical support, and collaborate cross-functionally to enhance Databricks' AI offerings.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The VP of Marketing & Acquisition will lead the acquisition strategy to drive growth, manage multi-channel campaigns, optimize performance through analytics, and ensure alignment across teams. Responsibilities include overseeing creative development, budget management, and customer engagement strategies, while demonstrating effective leadership and a focus on measurable goals.

The Enterprise Account Executive will drive the sales of Sift's fraud solutions to Fortune 1000 companies, engaging with key stakeholders and building custom strategies to address fraud challenges through value-based selling and collaboration.

Lead product strategy for AI-driven security operations, defining the vision and roadmap for agentic workflows, collaborating with teams, and measuring success metrics.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead development of end-to-end Machine Learning models for search and recommendation, collaborating with cross-functional teams and leveraging large scale data.

Own and execute the billing, financial, and corporate systems product roadmap. Define end-to-end experiences, lead 1-2 scrum teams, prioritize work using qualitative and quantitative data, and collaborate across Finance, Receivables, HR, analytics, UX and commercial teams to deliver automated, data-driven solutions that improve billing and financial functions.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and develop scalable ML infrastructure to improve healthcare.

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Develop core AI features for an AI-native product, including building LLM features, developing benchmarks, and overseeing the full lifecycle of development.

The Sales Engineer will serve as a technical lead, guiding clients on advanced data integration and analytics solutions in healthcare, impacting revenue and client engagement.