Top AI Engineer Jobs

This role involves optimizing power efficiency in GPUs using AI, analyzing power data, developing models, and collaborating across teams.

Lead performance and accuracy evaluation for scientific ML models (especially atomistic modeling). Identify bottlenecks, design scalable solutions like model parallelism, test and maintain AI-for-Science software, collaborate with HPC and research teams, and contribute documentation and educational materials.

Design and optimize CUDA-backed, large-scale ML training frameworks for scientific applications. Implement kernel-level acceleration, GPU porting, distributed learning, and maintain HPC stacks for atomistic modeling and generative ML while collaborating with infrastructure and research teams.

Design and implement MLIR-based graph representations, dialects, and compiler optimizations for GPU inference. Partner with framework and hardware teams, define APIs, perform performance analysis, and generate high-performance kernels for neural networks.

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 designing and scaling observability platforms, developing telemetry pipelines, and collaborating with engineering teams to ensure the reliability and performance of AI/ML systems.

Lead and manage the design and implementation of AI and SaaS platforms, ensuring security, reliability, and integration within the company's ecosystem while providing technical leadership.

The Proposal Engineer prepares power project proposals for datacenters and AI, collaborates across teams, defines proposal strategies, and engages with customers for technical feasibility and solutions.

Design and develop AI-driven software solutions at Emerson, integrating applications, collaborating with teams, and enhancing development practices, while thriving in innovation-driven environments.

Lead complex projects in software product development, ensuring on-time delivery and technical excellence while enhancing customer outcomes and stakeholder engagement.

Lead the design and development of AI algorithms and systems, optimizing them for both cloud and edge environments, and ensuring reliability and performance across platforms.

The Sr AI UX and UI Developer will design and implement user interfaces for AI applications, ensuring usability, performance, and scalability while collaborating with cross-functional teams.

The Sr AI Software Developer will design and develop advanced AI solutions, focusing on middleware, application services, AI workflows, and secure integration in a collaborative environment.

The Sr AI Platform Engineer designs and maintains AI platform infrastructure, implements cloud environments, develops IaC modules, and collaborates on AI solutions to enhance operational efficiency.

The Software Engineer II - AI/ML OPS Engineer will design and optimize ML pipelines, manage cloud infrastructure, and support Databricks operations, collaborating closely with engineers and data scientists.

The Sr AI Data Engineer at Honeywell will design and implement advanced data solutions for AI, support varied data needs, and collaborate with teams to enhance decision-making and operational efficiency.

Support machine learning operations and cloud projects, maintain CI/CD infrastructure, manage API deployment, and collaborate with cross-functional teams.

The candidate will design and maintain cloud infrastructure, implement CI/CD pipelines, optimize system performance, and mentor junior engineers in SRE and DevOps practices.

The Principal AI Data Engineer will design and implement data solutions for various AI modalities, optimize data pipelines, and support advanced data science activities. Responsibilities include building scalable systems, data governance, and collaboration with data teams for intelligent systems development.

The Lead Software Engineer will architect and implement software solutions for life safety platforms, focusing on AI integration and SaaS development, while mentoring engineers and collaborating across teams.

Design and develop AI systems for personalized travel and concierge services, focusing on integration and optimization of various technologies.

The Product Frontend Engineer will design and build scalable applications, collaborate with teams, and enhance frontend quality using AI tools.

The AI Solutions Engineer will develop AI prototypes, integrate Microsoft technologies, deliver production-quality code, and ensure alignment with enterprise architecture while demonstrating solutions to stakeholders.

Design and implement GenAI-powered business solutions integrating Microsoft Power Platform, Copilot Studio, and Azure OpenAI. Translate requirements into architectures, build and integrate production systems, develop documentation and diagrams, collaborate with architects, and support complex enterprise and federal client implementations.

Design, build, and deploy scalable generative AI systems to improve content metadata and personalization. Lead architecture, MLOps, RAG, prompt engineering, and evaluation; collaborate cross-functionally, integrate ethical AI practices, and monitor performance.