Top Remote AI Engineer Jobs

Lead the design and delivery of cloud-native applications and data platforms, ensuring high-quality software engineering and cloud operations.

As an Applied AI Engineer at Snorkel, you'll design and implement AI solutions using state-of-the-art techniques to solve customer challenges and enhance the Snorkel platform.

As a Software Engineer on the AI Core Team, you'll design and build AI pipelines and workflows, optimize systems, and collaborate cross-functionally to deliver advanced AI solutions. Requires proficiency in Python, JavaScript, and AWS services.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

Lead the delivery of AI solutions for clients, architecting robust systems, mentoring teams, and ensuring deployment success within the Salesforce framework.

Architect and implement reusable Angular UI frameworks and real-time chat components. Lead front-end engineering efforts, optimize performance and accessibility, integrate REST/WebSocket backends, support CI/CD and GCP deployments, and collaborate with Product, Architecture, and Design while mentoring peers.

The Software Engineer Sr Manager leads engineering teams, contributes to strategy, manages vendor relationships, mentors staff, and drives technology adoption and optimization across the enterprise.

Lead design and delivery of AI-powered prototypes and early production systems using LLMs, agentic workflows, and vector databases. Build end-to-end solutions (APIs, data pipelines, cloud deployments), integrate with Copilot/ChatGPT, drive POCs to production, and collaborate across teams to ensure responsible, scalable AI implementations.

The AI .NET Developer will lead the development of secure web applications using .NET, participate in Agile practices, and perform software analysis and design.

Lead the design of AI/ML architecture, develop scalable GenAI solutions, and provide technical guidance to teams while implementing best practices.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

You will build and maintain AI-native application features, working with a team of AI and backend engineers to ensure quality and innovation.

As a Principal Software Engineer, you'll own platform-scale initiatives, shape AI direction, ensure reliability in distributed systems, and mentor others.

Develop and implement AI-powered tools for automating survey research workflows, focusing on integrating AI technology and efficient data processing.

The Software Engineer will design and build AI-driven systems using Python and Java, focusing on machine learning and AI capabilities for enterprise data transformation and actionable insights.

The Senior Staff AI Software Engineer will architect an AI-native pharmacy benefits platform, focusing on software development, system design, and mentoring junior engineers.

As a Senior Product Engineer, you will develop web applications, APIs, and AI workflows, collaborating from conception to delivery and owning the entire process.

The AI Forward-Deployed Engineer is responsible for deploying agentic AI experiences within strategic customer accounts, ensuring measurable business outcomes through technical deployments and collaboration.

Design and build AI-powered features for a litigation platform, focusing on system reliability, scalability, and integration with existing systems. Optimize performance and champion engineering best practices throughout the development process.

Design and implement compiler IR, programming models, and optimizations for GPU-based AI inference; define public APIs; collaborate with hardware and framework teams to optimize performance, kernel generation, and build-time for Ahead-of-Time and Just-in-Time deployments.

The role involves developing and optimizing AI infrastructure for large-scale training and inference, ensuring system reliability and efficiency through software engineering practices.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Founding Software Engineer at Glacis, you'll lead engineering efforts, develop full-stack solutions, and drive AI integration while engaging directly with enterprise customers.

Design and implement compiler optimization algorithms for deep learning inference, collaborate with framework and GPU architecture teams, define public APIs, and deliver high-performance AOT and JIT compilation with reduced memory and fast build times.

Collaborate with AI/ML researchers to identify and fix infrastructure and application inefficiencies on GPU clusters; build tools and ML-based analyzers; monitor fleet utilization; optimize hardware, software, and distributed training/inference performance; and promote adoption of efficient AI/ML practices.