PromotedHiringCafe
ML Engineer - Inference & Model Deployment
Cupertino, CA, US
$250k-$310k/yr On-SiteFull Time
Turn powerful AI and ML models into fast, reliable production systems. Own inference latency, throughput, model-serving architecture, multi-GPU systems, and production deployment for millions of users.
Python, PyTorch, vLLM, SGLang, TensorRT, LLMs
PromotedHiringCafe
Founding Machine Learning / AI Search Engineer
Cupertino, CA, US
$160k-$310k/yr On-SiteFull Time
Build the ML and AI search behind HiringCafe — ranking, recommenders, retrieval, and LLM agents that surface jobs people would never find on their own.
Python, PyTorch, Elasticsearch, LLMs
PromotedHiringCafe
Founding Backend / Infra Engineer
Cupertino, CA, US
$160k-$300k/yr On-SiteFull Time
Own the crawlers, pipelines, and infrastructure powering a real-time job search engine. Strong Node.js and Python fundamentals; bonus points for security and reverse-engineering chops.
Node.js, Python, Elasticsearch, Redis
3w
Save
Mark Applied
Hide
Senior Site Reliability Engineer, AI Infrastructure
Mississauga or Salt Lake City
$139k-$155k/yr HybridFull Time
5+ YOE5+ years SRE/platform experience; strong observability and incident response; Terraform and GitOps; cloud platform experience (Databricks, Azure ML, Kubernetes); platform security and automation skills; strong communication.
Databricks, Azure AI, Azure ML, Kubernetes, Terraform, GitOps, CI/CD
6d
Save
Mark Applied
Hide
Sr. Applied AI Engineer
Salt Lake City, Utah, United States
OnsiteFull Time
5+ YOE5+ years software engineering with strong Python, 2+ years production ML/agentic AI, experience building agents, RAG, evaluation, safety, observability, and cloud infrastructure.
Python, FastAPI, LangChain, LangGraph, GraphQL, REST, PostgreSQL, Redis, Kafka, Kubernetes, AWS Bedrock, OpenTelemetry, Terraform, Langfuse, CrewAI, AutoGen
2d
Save
Mark Applied
Hide
Engineering Manager - Machine Learning
Toronto or London or Salt Lake City
$210k-$283k/yr RemoteFull Time
Hands-on technical manager/tech lead experience in MLOps, distributed systems, ML infrastructure, model deployment, GPU optimization, and mentoring engineers; familiarity with Python, PyTorch, containerization, orchestration, and cloud platforms.
Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA