Top AI Engineer Jobs

Design, implement, and scale AI/ML systems and data pipelines for healthcare applications. Own model inference, deployment, monitoring, and reliability; collaborate with cross-functional teams to deliver production ML solutions using cloud and distributed computing.

Lead adoption and delivery of AI/ML solutions (including LLMs, generative AI, chatbots, and predictive analytics). Design, build, deploy, and maintain cloud-hosted AI services, ensure responsible AI and compliance, provide technical leadership, mentor team members, and integrate AI into product and platform initiatives.

Lead design and hands-on implementation of scalable AI/ML systems for healthcare. Partner with cross-functional teams to define scope, deploy and monitor LLM/agent solutions, drive architecture and technical strategy, mentor engineers, and deliver production AI products that improve patient outcomes.

Design, implement, and operate production AI/ML systems for healthcare. Own inference and delivery of ML insights, scale and monitor models, build and optimize data pipelines, apply MLOps practices, and partner with cross-functional teams to integrate AI into products.

Architect, build, and deploy NLP, OCR, RAG and cloud ML solutions to modernize fax and telephony workflows; mentor teammates; collaborate with product and cross-functional teams; ensure secure, scalable production ML operations and monitoring.

Lead end-to-end AI/ML projects: research, prototype, optimize, and productionize ML and LLM solutions for healthcare. Mentor and recruit teams, run experiments and A/B tests, present results to leadership, and pursue AI research and IP.

Design, develop, test, and deploy generative AI/ML models (LLMs, RAG, agentic AI) into production using agent frameworks, containerization, CI/CD, and cloud platforms; analyze large datasets and optimize system performance.

Design, develop, and productionize NLP/ML/AI solutions (LLMs, NLU/NLG/SLU) for high-traffic consumer systems. Lead end-to-end model lifecycle: data ingestion, feature engineering, modeling, deployment, optimization, monitoring, and POCs. Establish best practices, prioritize work, and collaborate on scalable, voice-based bot platforms built on LLM frameworks.

Lead design, development, deployment, and maintenance of AI-powered solutions (LLMs, Generative AI, traditional ML) for provider-facing products. Build chatbots and conversational NLP, integrate AI into cloud (preferably AWS), ensure responsible AI practices and compliance, provide technical leadership, mentor engineers, and collaborate with product and architecture teams.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

The Lead Reliability Engineer will establish an AI Community of Practice, ensuring reliable service functionality and driving operational efficiency through data analysis and service management.

Lead the development of AI/ML systems for TIDAL, enhancing user experience through personalized recommendations and playlists while collaborating with cross-functional teams.

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

The iOS Engineer II will develop scalable Android features, collaborate with teams, optimize app performance, and ensure code quality.

Design, test, and optimize prompts for generative AI, collaborate with data scientists, analyze model performance, and improve prompt engineering processes.

The AI Platform Engineer Director will design and maintain scalable AI platforms, manage Kubernetes clusters, and ensure compliance across cloud services.

The AI Applications Engineer will prototype AI-driven solutions, collaborate with stakeholders, and create reusable components to address business challenges.

Lead technical projects for the Workers AI team focused on deploying AI inference, building innovative features, and enhancing developer experience.

The AI/ML Engineer will design, build, and deploy machine learning systems, optimize workloads, and ensure scalability and compliance of the ITMS platform.

The Senior Lead AI Engineer at Capital One will design, deploy, and support AI systems, working with cross-functional teams to innovate and enhance customer interactions while ensuring scalability and performance.

Lead design and development of enterprise AI/ML solutions, oversee model lifecycle, drive innovation, and mentor teams in AI engineering.

Develop and maintain a self-service MLOps/TPOps framework and reusable AI engineering components. Build MDLC capabilities, real-time and batch inferencing, APIs/microservices, CI/CD, observability, and hybrid cloud integration while guiding junior engineers.

The role involves designing and optimizing large-scale multimodal AI models, conducting applied research, and collaborating with cross-functional teams to deliver impactful member value at WHOOP.

As a Lakehouse Core Engineer, you'll enhance data systems, optimize storage and compute, develop ACID transactions, and improve query performance, focusing on petabyte-scale efficiency.

Lead the architecture and evolution of Granica's distributed data systems, focusing on efficiency, platform reliability, and team mentorship. Collaborate with AI teams and contribute to research in data infrastructure.