Top Machine Learning Jobs in Albuquerque, NM

Design, build, and operate production-grade AI systems using ML, LLMs, RAG, and agentic workflows. Define evaluation strategies, implement data/retrieval/orchestration layers, apply MLOps/LLMOps, and partner with stakeholders to prioritize, monitor, troubleshoot, and improve AI solutions balancing quality, latency, cost, reliability, and maintainability.

As a Principal Product Manager, you will drive innovation in AI technology, reshape expert acquisition strategies, and collaborate with cross-functional teams to enhance product offerings.

The Enterprise Account Executive will drive revenue by engaging with enterprise insurance clients, managing the sales cycle, and fostering strategic relationships with executives, leveraging Vellum's data analytics platform.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

The job involves selling AI and Machine Learning technologies to mortgage companies, managing the sales process for enterprise customers, and working with remote teams.

Lead development of AI-powered solutions, architect large language models, capture domain knowledge, and deliver client-focused insights. Manage a team to integrate AI capabilities across products.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Build and scale core components of an end-to-end proteomics software stack (LIMS, data pipelines, web portal). Design agentic backends and AI-augmented tooling, develop analysis algorithms and lab integrations, deploy cloud IaC and CI/CD, write tests and monitoring, and collaborate with R&D, operations, and customers to productionize tools for high-throughput proteomics.

The Principal Product Manager - Growth will lead growth initiatives, focusing on user engagement, retention, and the use of AI to enhance product strategies and experiences.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As a Regional Sales Director, you'll lead a sales team, develop business plans, and drive sales growth by managing complex cycles and nurturing talent.

Design and scale fraud-mitigation strategies for buyer, seller, and account fraud across Stripe products. Monitor portfolios, identify and predict risky behavior, propose controls, automate workflows, collaborate with Product/Engineering/Data Science, and educate users to minimize losses while enabling growth.

Lead product lifecycle for internal PaaS and Data-as-a-Service offerings focused on SRE and data engineering. Drive system reliability (99.99% availability), scaling strategies, GCP cost optimization, BigQuery/table and ETL performance, AI/ML enablement, and data governance/compliance across cross-functional teams.

Lead credit and funding decisioning for auto lending partners, exercising delegated lending and funding authority, resolving exceptions and stipulations, feeding performance insights to product and risk teams, conducting win/loss analysis, and enabling dealer-facing operations and training to protect portfolio performance and improve approval workflows.

Lead Buildertrend's end-to-end payments risk and operations: merchant onboarding, underwriting, transaction monitoring, disputes, chargebacks, and portfolio management. Build AI-assisted fraud prevention, scale automation, embed risk controls with Product and Engineering, develop analytics and governance, and grow a high-performing team to balance risk and business growth.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

The AI Sales Executive drives new business growth and expands client relationships by selling AI-driven solutions for engineering and manufacturing sectors, managing the full sales cycle with a consultative approach.

Own and implement end-to-end product features across the stack (React/TypeScript front end, Ruby on Rails backend, relational DBs, GCP infra). Design APIs and data models, ensure performance and reliability, integrate AI/LLM-powered features, collaborate with product/design/clinical teams, perform code reviews, and mentor junior engineers.

Own Oscilar's AML product suite (transaction monitoring, KYC/KYB, screening, case management, SAR filing, AI agents). Define detection rules, model calibration, data strategy, and defensible audit trails. Collaborate with engineers and compliance, use AI across discovery/design/analysis, deliver PRDs, validate models, and ship production features.

Lead high-impact strategy and BizOps workstreams including M&A diligence, investor relations, new-market expansion, and cross-market operations. Frame ambiguous, board-level problems, build analysis and recommendations, align stakeholders, and own execution end-to-end while leveraging AI and automation.

Lead enterprise solution architecture for the CMS HIGLAS/HOM program: define multi-year roadmaps, modernize Oracle ERP (EBS, Hyperion) across OCI and hybrid clouds, design integrations and AI/ML analytics pipelines, ensure security/compliance (HIPAA, FedRAMP), oversee data migration and HA/DR, run architecture reviews, and mentor teams through delivery and transformation.

This is a general talent-community application inviting candidates across many functions to submit resumes. Recruiting will review and retain applications for future openings; candidates should highlight experience, accomplishments, and interests for potential remote roles.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.