Top Remote AI Engineer Jobs

Design and implement a virtual access layer to enable remote use of a physical AI lab, building scalable, secure infrastructure to process 100,000+ documents/day with LLMs, optimize GPU/LLM throughput, provide customizable interfaces, implement authentication/access controls, and lead projects from design to production.

Design and develop a C++-based system for simplifying and accelerating computing in DL and HPC, alongside evaluating performance and improving library quality.

Customer-facing technical role supporting AI/ML initiatives across US Major Accounts. Architect and prototype AI/ML solutions, build MVPs and PoCs, support regional SE teams, deliver technical presentations and workshops, and upskill teams. Travel ~30-40% to support customer engagements.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Build and optimize high-traffic, responsive web applications and hybrid in-app pages. Implement user-facing features, improve performance and scalability, and create libraries/frameworks to accelerate development and enhance code quality.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Design, build, and maintain high-performance backend services and APIs using Java/Spring Boot. Develop and productionize recommendation algorithms and LLM systems, optimize LLM workloads (including on-prem), ensure scalability, reliability, and security, and collaborate across time zones with product and project teams to own end-to-end architecture.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

Responsible for functional and API testing of platform products, designing and executing end-to-end tests across frontend, backend, strategy, and algorithms. Validate personalized user experiences, improve test coverage and QA processes, and drive adoption of AI-assisted test generation and automation. Collaborate with Product, Engineering, Algorithm, and Strategy teams to identify issues and ensure quality.

As a Founding AI/Data Engineer, you'll design and build AI-driven products, collaborate across teams, and ensure system reliability while enhancing user experiences.

Lead development, refactor, test, deploy, and maintain production software; collaborate with product teams in agile processes; integrate AI-assisted tools and ensure security, resilience, performance, and monitoring; create test suites; mentor and guide junior engineers.

Develop, test, deploy, and maintain production software within an agile team. Participate in product configuration, security, resilience, performance tuning, and monitoring. Learn and adopt AI-assisted development tools and collaborate cross-functionally to meet shared objectives.

Lead a product engineering team to design, build, deploy, and maintain production software. Drive architecture, testing, resilience, security, performance tuning, and mentor junior engineers while collaborating with product and cross-functional teams.

Embed with finance teams to architect and deploy AI-enabled workflows (LLM agents, retrieval pipelines) integrating APIs and internal systems; ensure HIPAA-compliant designs, lead adoption/training, establish telemetry, and troubleshoot and optimize workflow performance.

Senior technical lead for APAC partners driving partner enablement, co-selling, and technical leadership around Talkdesk CCaaS/CXA. Responsibilities include advanced demonstrations, solution design, ecosystem integrations, Agentic AI implementations, partner competency development, and regional representation with ~35-70% travel.

Lead backend development and architecture in Laravel/PHP while embedding AI as a core system layer. Build AI agents, prompt pipelines, vector search, and automated workflows integrating third-party services. Optimize APIs, databases, and scalable, secure systems. Mentor engineers and collaborate with product and data teams to deliver reliable AI-powered features.

Build production-grade software using AI as a primary development partner: convert requirements into prompts and implementation plans, generate and validate AI-produced code, create tests, ensure security and maintainability, build reusable prompt/templates and workflows, and guide teams adopting AI-native engineering practices.

Lead operations for large-scale AI infrastructure: manage NVIDIA GPU and high-performance networking environments, troubleshoot Linux/Kubernetes/storage/hardware issues, drive incident response and root cause analysis, improve observability and automation, mentor engineers, and collaborate with engineering and datacenter teams to ensure platform reliability and scalability.

Early-career full-time program offering training, mentorship, and hands-on work within Binance's blockchain ecosystem. Participants develop practical skills in Web3, collaborate across teams, and contribute to product and engineering projects while receiving tailored curriculum and 1:1 mentorship.

Lead architect and hands-on builder for AI solutions: evaluate feasibility and data readiness, translate business problems into technical and algorithmic requirements, design high-level architectures and prototypes, drive PoC to production handover, set MLOps/API standards, mentor team, and align North American implementations with European enterprise governance.

Define and build Fuse's inference-serving architecture and stack, including request routing, batching, scheduling, and autoscaling for latency-sensitive workloads. Own model-level optimizations (quantisation, distillation, speculative decoding), translate performance SLAs into capacity plans, and integrate low-level GPU/CUDA performance work with serving infrastructure. Set benchmarks, tooling, and act as technical owner of inference performance and reliability.

Design, build, and operate end-to-end data and AI systems: scalable ETL pipelines, model development and deployment, backend services/APIs, cloud infrastructure, MLOps, data governance, and lead technical reviews while mentoring engineers and collaborating with stakeholders.

Design and optimize AI communication middleware for distributed multi-node, multi-GPU training. Implement C/C++ performance-critical features, improve GPU communication paths, profile and tune frameworks (PyTorch, TensorFlow, JAX, DeepSpeed), develop benchmarks, contribute upstream, and collaborate with kernel, driver, switch, and systems teams to validate and deploy high-performance networking for AI/HPC.

Lead hands-on AI development and deployment to automate Salesforce administration and improve sales effectiveness. Build, evaluate, and deploy LLM-based use cases (Gemini, Agentforce), integrate multi-source data securely, collaborate with Salesforce IT and cross-functional teams, and measure success by reduced manual administrative effort and successful AI deployments.