Top Remote Machine Learning Engineer Jobs in Denver & Boulder, CO

Lead design, development, and deployment of production-grade, large-scale ML systems. Influence ML strategy, integrate models with platform and data infrastructure, mentor engineers, communicate results to stakeholders, and mature ML infrastructure and abstractions across teams.

Lead design, development, and deployment of large-scale production ML systems and platform strategy. Research and prototype ML and big-data technologies, integrate ML services across the org, mentor engineers and data scientists, and communicate complex ML solutions to technical and non-technical stakeholders.

Lead technical direction and delivery of ML platform infrastructure (feature store, model serving, experimentation, training pipelines). Drive architecture, resolve system-level issues, write production code, mentor engineers, and partner with ML, data, and product teams to enable scalable, reliable ML model development and deployment.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

As a Principal Software Engineer, you'll architect and code backend services and ML models, integrate them with Salesforce, and mentor junior engineers.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Build and operate ML training and serving infrastructure; design, develop, and launch backend systems; collaborate across teams to decompose projects; maintain availability through monitoring and on-call support; review and debug large codebases; contribute to hiring and team growth.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

Design, build, and productionize large-scale ML models and pipelines for search and recommendations. Collaborate with engineers, product managers, and data scientists to define requirements, develop features, run experiments, and measure impact. Maintain low-latency serving, reproducible training, and scalable data infrastructure for personalization and relevance.

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

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

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.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

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 Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.