Find your next AI Engineering role
2+ open roles · 364+ companies hiring
2 open positions
Technical Lead, Artificial Intelligence
Parallel Wireless
We are building the AI layer of the Radio Access Network, applying agentic AI, machine learning, and LLMs to real RAN challenges. This role is for a Technical Lead to own the end-to-end architecture and technical direction of these AI systems. It is a hands-on senior individual contributor role, combining architecture, coding, technical leadership, and mentorship. You will work alongside RAN, PHY, and software teams, building production-grade AI solutions for real cellular networks.
AI-Driven 4G PHY SW Engineer
Parallel Wireless
Parallel Wireless is seeking a driven PHY SW Engineer to join their R&D team. This role will focus on developing advanced, carrier-grade 4G cellular communication solutions, emphasizing performance, reliability, and AI-driven development. The engineer will contribute to building the software behind next-generation cellular networks and shaping the future of telecommunications through innovative and sustainable solutions.
Frequently asked questions
What counts as an AI Engineering job?
AI Job Board lists engineering roles that build, deploy, or operate AI/ML systems — including LLM engineering, RAG (retrieval-augmented generation), AI agents, prompt engineering, AI infrastructure and MLOps, model serving/inference, and fine-tuning. It excludes non-engineering functions like AI sales or marketing roles.
What is the difference between an AI Engineer and a Machine Learning Engineer?
An AI Engineer typically builds applications on top of existing models — LLM integration, RAG pipelines, agent orchestration, and prompt design. A Machine Learning Engineer more often trains, fine-tunes, or productionizes custom models. Many companies use the titles interchangeably, so search both when browsing.
Does AI Job Board include AI infrastructure and MLOps roles?
Yes. Titles such as AI Infrastructure Engineer, ML Platform Engineer, GPU Infrastructure Engineer, Inference Engineer, MLOps Engineer, and AI Site Reliability Engineer are all covered — these roles focus on the systems that serve and scale AI models rather than building models themselves.
Are remote AI and ML jobs available?
Yes. Filter by "Remote" on the jobs page to see fully remote AI/ML engineering roles, or browse the remote jobs feed directly.
What skills are most in demand for AI engineering roles?
The most commonly requested skills are LLM APIs (OpenAI, Anthropic, Gemini), RAG and vector databases (Pinecone, Weaviate, Qdrant), agent frameworks (LangGraph, CrewAI, AutoGen), inference/serving tools (vLLM, Ray Serve, TensorRT-LLM), and fine-tuning. Use the skill filters on the jobs page to browse by specific technology.
How fresh are the job listings?
Listings are sourced continuously from company career pages and refreshed automatically. Each job shows when it was posted, and the sitemap and API expose last-updated timestamps for every posting.
How much do AI Engineers get paid?
Compensation varies widely by role, seniority, and location. Where employers disclose a salary range, it is shown directly on the job listing — filter by salary range on the jobs page to narrow results to your target compensation.