Offer summary

Qualifications:

Bachelor's or higher degree in Computer Science, Engineering, or related field., At least 5 years of experience building production systems in Python, TypeScript, or Rust., Over 1 year of experience delivering AI or LLM features to external users., Strong knowledge of machine learning tooling such as PyTorch, TensorFlow, and transformers..

Key responsibilities:

Architect and develop cloud-native services integrating real-time data streams with AI models.

Manage the full machine learning lifecycle including training, evaluation, and deployment.

Create internal tools and SDKs to simplify AI integration for teams.

Optimize AI inference for sub-100 ms latency at a global scale.

Job description

About PubNub
PubNub powers the world’s most engaging real-time experiences—chat, live updates, and interactive applications—for over 2,000 companies including Verizon, Autodesk, Zillow, and Dropbox. Our global data network processes trillions of messages each month with sub-100 ms latency across 15+ data centers. Backed by $130M in funding, we’re shaping the future of how the world connects.

We’re now building something new: an intelligence layer that lets developers weave large language models (LLMs) and deep-learning pipelines directly into high-speed streams. We believe AI should be as real-time as the data it reasons about, and we’re hiring founding engineers to make that vision real.

The Role
As a Senior AI Engineer, you’ll architect and build cloud-native services that combine PubNub’s real-time streams with state-of-the-art AI. From retrieval-augmented generation and low-latency inference to developer tooling, you’ll create the foundation of PubNub’s intelligence platform. This is a greenfield opportunity to define architecture, drive scale, and deliver AI capabilities that power products across industries.

What You’ll Do

Architect and build services that fuse real-time data streams with NLP, moderation, recommendation, and custom models
Own the full ML lifecycle: pipelines, fine-tuning, evaluation, packaging, inference, and observability
Develop internal tooling (SDKs, CLI, CI/CD hooks) so teams can add AI with a single API call
Optimize for sub-100 ms inference at global scale using CUDA, TensorRT, vLLM, Rust, and caching strategies
Partner with product and solution architects to deliver reusable AI capabilities: content safety, sentiment, personalization, anomaly detection, and more
Champion responsible AI practices: robust evaluation, guardrails, governance, and transparent feedback loops

What We’re Looking For

Required

5+ years building production systems in Python, TypeScript, or Rust (ideally more than one)
1+ year delivering AI/LLM features to external users
Experience scaling services beyond 100k req/s or equivalent event volumes
Deep knowledge of ML tooling (PyTorch/TensorFlow, transformers, vector search, distributed training, experiment tracking)
Strong containerization/orchestration skills (Docker, Kubernetes)
Comfortable using AI coding copilots as part of your workflow
Excellent written and verbal English communication

Preferred

Experience with streaming platforms (Kafka, Kinesis, Redpanda)
Hands-on work with cloud AI services (AWS Bedrock, GCP Vertex, Azure OpenAI)
Knowledge of low-level performance tuning (CUDA kernels, SIMD, memory profiling)

Why Join PubNub

Build a greenfield intelligence platform at internet scale
Ship features that land directly in customer-facing products across healthcare, fintech, gaming, and streaming
Competitive Compensation in the range of USD149000-200000
Remote-friendly culture with Open PTO
Equity in a profitable, fast-growing infrastructure company
A team that values craftsmanship over ego

If you’re excited to make AI real-time, we’d love to hear from you.

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