Top Machine Learning Jobs in Tucson, AZ

Lead client-facing architecture and delivery of production-grade GenAI systems. Design scalable LLM, agentic, RAG, recommender, and LTR solutions, manage client engagements, mentor ML engineering teams, and oversee project lifecycle from discovery to deployment and monitoring.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

As a Senior/Staff ML Systems Engineer at Quilter, you'll design and maintain ML infrastructure for automated PCB component placement, manage data pipelines, and lead systems design reviews while ensuring project efficiency and reliability within a fully distributed team.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

As a Senior Machine Learning Engineer, develop LLM evaluation frameworks and agentic AI workflows to extract insights from conversations and optimize customer experiences.

Build and operate high-throughput experimentation and recommendation infrastructure. Design APIs and services, use agentic AI workflows (LLMs) for development, ensure performance and reliability, participate in on-call, mentor teammates, and codify AI-native engineering practices.

As a Machine Learning Engineer, you'll design and implement detection systems, enhance model efficacy, and analyze datasets to improve email detection against security threats.

Lead R&D on LLMs for edge AI: design efficient LLM architectures, training and post-training algorithms, reasoning and agentic models, apply LLMs to code generation and tool-enabled automation, and collaborate with systems and business teams to deploy AI/ML solutions.

The Senior Manager, Data Science/ML will lead a team to enhance product innovation through data science, focusing on ML and experimentation frameworks that boost customer engagement. Responsibilities include defining product strategy, building ML models, and collaborating with cross-functional teams to shape product roadmaps.

Lead development and maintenance of internal Python SDK frameworks and agentic workflows, build scalable FastAPI-based ML APIs, automate CI/CD with Jenkins and GitLab Runners, use Galileo for model evaluation and observability, and collaborate across teams to deliver production-grade autonomous systems.

Lead design, build, and production deployment of ML and GenAI solutions (LLMs, RAG, multi-agent systems, recommender and RL models). Architect scalable, secure inference and MLOps pipelines, mentor MLEs, collaborate with stakeholders to define roadmaps, and measure model performance and business impact. Implement fine-tuning, retrieval, orchestration, and monitoring for enterprise-grade AI products.

The role involves managing the ML lifecycle, developing scalable ML systems, and collaborating on AI-first product solutions focusing on Large Quantitative Models.

The role involves owning and delivering AI-powered features for Calendly, collaborating with multiple teams, and applying machine learning solutions for product enhancement.

The AI & Machine Learning Director will lead client engagements, analyze corporate performance, and drive improvements in profitability through machine learning and data analysis, while also managing business development and team collaboration.

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

The role involves product management of AI tools, collaborating with research, engineering, and design teams to develop and enhance products, focusing on user needs and market value.

Lead and mentor engineering teams while owning platform architecture (React, Node/Express, Postgres, AWS). Drive TypeScript migration, design ETL and AI/LLM integration frameworks, ensure reliability and observability, manage delivery, incidents, and hiring, and define technical strategy for production ML/AI systems.

Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders.

SoftSnow is seeking an AI Ethicist to define ethical guidelines, assess risks, and ensure compliance in AI implementations across various industries.

Design and implement NLP and LLM-powered pipelines to extract, summarize, and semantically search technical documentation. Fine-tune transformer models, build RAG systems, convert unstructured documents into structured knowledge, optimize inference for production, and collaborate with engineers and SMEs to deploy document intelligence solutions.

The Senior Data Engineer will own the data strategy, managing sourcing, structuring, and optimizing multimodal data to enhance AI models and products.

As a Senior Software Engineer, you'll build and operate the ML platform, optimizing data operations, managing the feature store, and supporting ML initiatives while driving architectural roadmap decisions.

The Staff Engineer will architect and build AI and ML infrastructures, mentor engineers, and lead high-impact initiatives to enhance ML capabilities across Attentive's platform.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.