Top Remote Machine Learning Jobs in Tucson, AZ

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.

Partner with customers to design and deliver production-ready AI/ML solutions, drive POC-to-production success, troubleshoot technical issues, inform product roadmap with customer feedback, and communicate outcomes to stakeholders.

Develop and productionize consumer-facing AI features using LLMs. Collaborate across the AI stack, run A/B tests and evaluations, improve model reliability and guardrails, and optimize latency, cost, and scalability of production AI systems.

Develop AI/ML-powered features in ClickHouse Cloud, focusing on frontend and API architecture, UI/UX, and integrations with AI systems.

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 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 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 Director of AI & ML is responsible for establishing and leading the AI function, defining AI strategy, building a high-performing team, and delivering production-grade ML and AI solutions within healthcare payer workflows.

Lead design, build, and operation of end-to-end production ML systems (feature pipelines, training, inference, experimentation, monitoring) for ranking, recommendation, rewards, ROAS/LTV prediction, personalization, and offer optimization in a high-scale AdTech environment. Provide hands-on technical leadership, mentor engineers, drive MLOps and observability standards, and partner with Data Engineering, BI, Product, and business teams to connect models to outcomes.

Lead and oversee multiple AI/ML modeling workstreams, managing full model lifecycle, governance, validation, and performance. Provide strategic technical leadership, translate results for stakeholders, evaluate AI tools, recruit and mentor modelers, and align models with business and regulatory requirements.

Design and productionize ML models and agentic systems for intraday financial alpha generation. Build data pipelines, experiment frameworks, and portfolio optimization methods. Collaborate with quants and engineers to move models from research to live trading environments.

Lead end-to-end ML system development: data exploration, model research, training, deployment, evaluation, and MLOps. Collaborate cross-functionally to prioritize claims, improve matching, measure business impact, and own a technical workstream.

Lead design, development, and production deployment of ML and generative AI solutions at scale. Drive personalization, pricing, experimentation, agentic AI, and simulation modeling. Partner with engineering and product teams, mentor engineers, influence technical strategy, and measure business impact through data-driven experimentation.

The Sales Executive will develop new AI and ML service opportunities, manage sales pipelines, and engage with technical decision-makers primarily in the US and Canada. Responsibilities include proposal shaping, pipeline management, and client relationship management with a focus on complex technology sales.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

Lead GoDaddy's three-year Generative AI and ML roadmap, architecting and scaling agentic and personalized AI solutions globally. Own end-to-end ML systems, enable rapid experimentation, ensure governance/compliance, and partner across product, engineering, and analytics. Mentor and grow high-performing teams and drive adoption of advanced AI techniques to improve customer experiences and business outcomes.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

Join an R&D team to develop image-processing and computer-vision algorithms for 2D/3D scene segmentation, design experiments to detect long-tail model failures, and explore deep learning models and active learning methods to improve autonomous robotic vision systems.

Lead development of internal Python SDKs and agentic AI workflows, build scalable FastAPI ML services, maintain CI/CD with Jenkins/GitLab Runners, and use Galileo for model evaluation and observability to productionize autonomous systems.

The Staff Engineer will design and manage ML infrastructure while mentoring teams, driving MLOps strategies, and ensuring compliance in healthcare data systems.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Lead program delivery for engineering teams at Arine, optimizing internal processes and ensuring timely execution of technical programs while facilitating Agile methodologies.

Design and develop machine learning systems for construction robots, including scalable infrastructure, computer vision models, and data analysis for performance improvement.