Top Remote Machine Learning Jobs in Albuquerque, NM

Leads AI/ML research and development, owning enterprise evaluation methodology, predictive and decision models, experimentation, causal inference, model economics, and production deployment. Builds evaluation suites and models hands-on, monitors performance and cost, prototypes agentic techniques, and guides AI-native engineering practices. The role also develops a small team, raises organizational ML fluency, supports data-as-a-service benchmarks, and communicates model uncertainty and business value to executives.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Own and negotiate complex commercial transactions, including customer agreements, research collaborations, partnerships, data licenses, SaaS contracts, vendor agreements, and professional services agreements. Partner with sales, science, finance, and R&D teams, particularly on life sciences and computational chemistry deals. Build scalable legal infrastructure through playbooks, templates, fallback positions, self-service processes, and AI-enabled contract workflows.

Build, fine-tune, evaluate, and deploy computer vision and multimodal machine learning models in production. Develop scalable data pipelines, evaluation frameworks, real-time processing systems, and cloud infrastructure with monitoring and automated scaling. Improve image processing, barcode decoding, and OCR capabilities while partnering with engineering and fulfillment teams. Contribute through code reviews, documentation, testing, technical leadership, and mentorship.

Leads Lexia’s business analytics and data strategy function, managing analysts and overseeing data engineering alignment. Owns BI strategy, Tableau governance, data governance, self-service dashboards, AI-enabled analytics, metric definitions, and data quality. Partners with Sales, Marketing, Customer Success, executives, and analytics engineering to translate business needs into insights, KPIs, models, and actionable recommendations. Manages analytics tools and vendors while ensuring responsible, secure, and effective use of enterprise data.

Lead the evolution of trading infrastructure by managing trade operations, P&L attribution, risk monitoring, data integrity, and performance reporting. Develop Python- and machine-learning-based AI agents, MLOps workflows, anomaly detection, predictive risk models, automated reconciliations, and real-time dashboards to transform manual trading operations and improve risk analysis.

Leads clinical intelligence initiatives by sizing AI opportunities, conducting data discovery, evaluating AI/ML solution performance, and measuring impact, accuracy, drift, and patient outcomes. Partners with product, clinical, engineering, compliance, and operations teams to develop measurement plans, value hypotheses, benchmarks, and scalable intelligence capabilities. The role is remote with occasional travel and requires advanced SQL, Python, clinical analytics, and population health research expertise.

Write technically accurate case studies, articles, product explainers, launch materials, and social content for AI engineers, researchers, and technical leaders. Interview customers, partners, and internal experts; learn HUD’s platform and workflows; explain technical products and research clearly; support founder communications; manage content from ideation through publication; and improve content using reader and go-to-market feedback.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Owns the infrastructure and production lifecycle for product and marketing machine learning models. Responsibilities include real-time model deployment, feature pipelines and stores, monitoring and alerting, CI/CD, retraining infrastructure, marketing model operationalization, data pipelines, ad-platform feedback loops, and dependency management. The role bridges data science and engineering while mentoring teammates and making pragmatic architecture decisions.

Lead the Machine Learning Ranking team, managing data scientists and ML engineers while driving career development, technical quality, and product outcomes. Partner with Product Management and Decision Science to define roadmaps, metrics, and marketplace experiments. Oversee machine-learning pipeline development, model deployment, and performance monitoring. Provide technical guidance on ML and AI applications, evaluate engineering work, and promote scalable, reproducible practices across the team.

Leads DISCO’s machine learning research strategy, directs advanced algorithm and methodology development, oversees large-scale research programs, and manages research teams. Collaborates with industry partners and cross-functional stakeholders to apply machine learning to real-world challenges. Develops long-term research plans, mentors researchers, optimizes research processes, and contributes to the broader research community through publications, presentations, and industry engagement.

Develops predictive models, machine learning solutions, data pipelines, statistical analyses, and internal data applications. The role uses Python and SQL Server to analyze structured and unstructured data, applying NLP, classification, regression, clustering, automation, and AI/LLM techniques. Responsibilities include maintaining data science platforms, supporting cross-functional decision-making, and communicating technical findings to non-technical audiences.

Leads financial strategy, planning, forecasting, and operating cadence across Sales, Marketing, Customer Success, and GTM Operations. Owns GTM economics, sales compensation, commissions forecasting, executive reporting, driver-based modeling, resource allocation, and profitability analysis. Modernizes Finance through AI, automation, advanced analytics, improved controls, and scalable processes while developing the GTM Finance team and advising senior executives.

Leads automated scoring and natural language application research for educational assessment products. Responsibilities include setting team priorities, mentoring scientists, designing and analyzing studies, developing machine learning applications, collaborating with stakeholders, presenting technical findings, writing reports, publishing applied research, and supporting products involving automated scoring, crisis-content detection, and formative feedback.

Evaluate, deploy, and optimize machine learning models for on-device execution on Android phones. Benchmark models on mobile hardware, optimize latency, memory, and power consumption, and apply quantization, compression, and distillation. Integrate models with Android applications, system services, and AI agent runtimes. Build hybrid local/cloud model routing and determine which workflows should run locally versus through cloud inference.

Defines and leads architecture standards for production machine learning, generative AI, LLM, and agentic systems. Establishes lifecycle management, observability, evaluation, safety, security, operational readiness, support ownership, and governance practices. Partners with engineering, product, data, security, infrastructure, and IT support teams to deliver reliable AI capabilities. Provides hands-on technical leadership, architecture reviews, documentation, mentoring, prototyping, incident support, and guidance on RAG, vector search, model gateways, prompt orchestration, and agent workflows.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Early-career Data Scientist supporting supply chain transformation through machine learning, forecasting, statistical modeling, data preparation, dashboards, and AI solutions. The role addresses inventory optimization, demand forecasting, production planning, delivery performance, and cost reduction. Responsibilities include developing analytical datasets and workflows with Python and SQL, evaluating models, integrating enterprise data, supporting cloud-based analytics, and communicating insights to business stakeholders in a manufacturing environment.

Own the technical sales cycle for Databricks consulting engagements, including discovery, architecture design, solution scoping, estimation, proposals, demos, proofs of concept, workshops, and statements of work. Design lakehouse, data engineering, analytics, governance, security, and AI architectures. Partner with sales, Databricks, alliance, and delivery teams while ensuring effective handoffs into implementation.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads high-visibility product programs focused on market adoption, analyst relations, customer advisory boards, executive briefings, and industry events. Translates technical product roadmaps into compelling market value propositions, synthesizes analyst and customer feedback, and provides actionable insights to product leadership. Partners cross-functionally with Product, Marketing, and executive stakeholders while supporting strategic initiatives and external-facing communications.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.

Build and deploy mechanistic, hybrid, and data-driven models for pharmaceutical CMC processes, including drug substance, drug product, packaging, labeling, technology transfer, and manufacturing. Integrate process and experimental data into FAIR data products, analytics, dashboards, and AI-enabled tools. Partner with technical teams and CDMOs to support process understanding, forecasting, risk assessment, regulatory filings, and technology-transfer decisions while owning the digital roadmap and mentoring colleagues.