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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
3mo
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Distinguished Data Engineer (Marketing Technology)
McLean or Richmond or Chicago or New York
$245k-$335k/yr OnsiteFull Time
7+ YOEBachelor's degree; 7+ years data engineering; 3+ years data architecture; 2+ years AWS; plus preferred: Master's, 9+ years data engineering, 3+ years data modeling, 2+ years ontology standards, 2+ years Python/SQL/Scala, 1+ year ML deployment, 3+ years AWS big data.
AWS, Python, SQL, Scala, Ontology standards
1mo
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Gen AI Engineer
Atlanta or Richmond or Lake Mary or Nashville or Indianapolis or Wilmington or Mason or Grand Prairie or Norfolk or United States
HybridFull Time
4+ YOEBachelor's in a quantitative field (or equivalent) and 4+ years experience; advanced Python and SQL; hands-on experience with LLM/GenAI, NLP, Hugging Face, TensorFlow, Keras, PyTorch, Spark; cloud (GCP/AWS) and MLOps/model deployment experience.
Python, SQL, Hugging Face, TensorFlow, Keras, PyTorch, Spark, GCP, AWS, vLLM, Text Generation Inference, FastAPI, GPTQ, AWQ, bitsandbytes, AWS EKS, AWS ECS, GCP GKE, Azure AKS
1w
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Senior Power Platform Developer
St. Louis or Fort Lee
RemoteContract
6+ YOEActive Secret clearance, 6+ years BI/analytics/application development experience with 4+ years Power BI and 2+ years Power Apps/Power Automate; strong DAX, Power Query/M, SQL, data modeling, and Power Platform deployment skills.
Power BI, Power Apps, Power Automate, DAX, Power Query/M, SQL, Dataverse, SharePoint, Azure, Azure Functions, GCSS-Army, SAP, Power BI deployment pipelines, Power Platform, Army 365, GCC High, Microsoft Government tenant
3mo
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Principal Data Scientist, Operations
Richmond or United States
$183k-$224k/yr RemoteFull Time
3+ YOEPhD with 3+ years or BS/MS with 7+ years in quantitative field; hands-on ML model deployment; Python stack; strong software engineering practices.
PyData stack (numpy, scikit-learn, pandas)