1,081 total jobs
178 new jobs this week
Research and engineer vision-language models across the development lifecycle, from multimodal data curation and training to evaluation and optimization for capable, efficient real-world deployment.
Lead the architecture and hands-on delivery of AI solutions in production, including LLMs, agents, and RAG, while mentoring developers and setting standards for scalable, reliable, observable systems.
Build and deploy production AI systems for client and internal teams, translating ambiguous business problems into technical scope while contributing reusable agents, skills, and tooling to Netguruโs AI platform.
As an AI Engineer, you will design, develop, and deploy AI-powered solutions that support industrial automation, smart manufacturing, and digital transformation initiatives.
As a Principal Rendering Engineer, you will design and maintain high-performance rendering technology, optimizing graphics systems for AAA games and real-time simulations.
Build and scale production-ready AI applications and platforms, translating ambiguous business needs into robust systems while contributing across backend, cloud, and AI workflows.
Create exceptional illustrations using Generative AI for leading brands, combining strong visual storytelling with established brand systems.
Build AI-powered workflows and tools across business functions, coach teams toward confident independent AI use, and establish reusable practices, adoption tracking, documentation, and governance.
Develop and scale pre-training architectures for LLMs and multimodal models, advancing cross-modal understanding through data curation, experimental research, and optimization of distributed training.
Develop and scale pre-training architectures for LLMs and multimodal models, curate large-scale datasets, and optimize distributed training to improve model intelligence, efficiency, and cross-modal performance.
Develop and scale architectures, data pipelines, and training methods for large language and multimodal models, advancing pre-training performance, efficiency, and cross-modal understanding.
Drive research and development of LLM and multimodal architectures, leading large-scale pre-training, data curation, experimental optimization, and distributed training improvements to advance model capabilities and efficiency.
Develop and scale pre-training methods, architectures, and data pipelines for large language and multimodal models, improving model intelligence, cross-modal understanding, training efficiency, and distributed scalability.
Develop and scale architectures, training methods, and data pipelines for large language and multimodal models, improving model intelligence, efficiency, and cross-modal performance.
Develop and scale pre-training architectures for large language and multimodal models, improving intelligence, efficiency, and cross-modal performance through research, data curation, and distributed training.
Architect marketing data infrastructure and AI-enabled data products, building reliable pipelines, semantic models, and agents that power self-serve analytics and automate workflows across Marketing and go-to-market teams.
Build and deploy custom AI agents and intelligent workflows for client fraud, compliance, and financial-crime challenges, owning solutions from requirements gathering through production and performance evaluation.
Design and deploy machine learning systems, optimizing models for image and video processing while collaborating with cross-functional teams to deliver scalable ML solutions.
Develop and implement an AI orchestrator with a focus on LLM-based assistants, prompt engineering, and API integration in a 3-month project.
As a Staff Machine Learning Engineer on the Identity Verification team, you'll lead the development of ML systems that ensure the legitimacy of users and documents at Coinbase.
Design, build, evaluate, and operate AI capabilities for an enterprise platform, including agents, RAG, and semantic search, while developing production backend services with C# and.NET.
Design, build, evaluate, and operate production AI capabilities, including agent platforms, RAG, semantic search, and copilots, while developing reliable C#/.NET services and improving AI quality, security, and performance.
Own end-to-end delivery of customer-facing AI features, from prototypes and prompt experiments to reliable production systems and polished product experiences that improve hiring workflows.
Build and scale machine-learning and generative AI products for utility-sector use cases, developing reusable pipelines, agentic systems, and evaluation frameworks in collaboration with data scientists and software engineers.
Those that list pay offer a median of $190,000 a year. The middle half pay between $165,000 and $225,000.
| Level | Range | Middle half ยท median |
|---|---|---|
| Mid-level | $139Kโ$218K ยท $184K | |
| Senior | $167Kโ$222K ยท $190K | |
| Lead | $194Kโ$245K ยท $220K |
30% of these listings post pay. From 125 listings with pay in USD, at most three per company.
5% of these listings are open worldwide and 2% to a whole region, like Europe or Latin America. The other 93% hire in specific countries:
From 927 listings that state where they hire.
What hiring companies here ask for far more often than across all remote jobs, so it is worth putting front and center on your resume.
Share of the 431 companies hiring here that ask for each skill, and how many times as often as across all remote jobs. Soft skills like communication are left out.
Half stop taking applications within 34 days of being posted, and 1 in 4 within 12 days. Applying in the first week counts.
12 days
1 in 4 closed by then
34 days
Half closed by then
76 days
3 in 4 closed by then
From 530 listings that closed in the last 120 days, at most three per company.
