Senior ML Platform Engineer

Latitude; Atlanta (GA); Hybride; USD 163 000 - 343 000; Plein temps

Avantages offerts par ce poste

Employee ownership

Health insurance

401k with matching

Disability insurance

Paid time off

Growth opportunities

Résumé du poste

Omnissa, the AI-driven digital work platform, is hiring for an ML Engineer on the AI Platform Team. Location: Mountain View, CA or Atlanta, GA, hybrid work. You will design, deploy ML models, build data pipelines, and improve model performance at scale.

Requirements include 5+ years in ML engineering or data science, strong Python (PyTorch, TensorFlow, Scikit-learn), cloud experience (AWS/Azure/GCP), Docker/Kubernetes, and hands-on with LLMs and vector databases. Competitive USD salary.

Qualifications

• five+ years of experience in machine learning engineering or data science roles.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Sci-kit Learn).
• Experience building/operating data workflows (batch/streaming) and cloud platforms (AWS/Azure/GCP).
• Knowledge of ML algorithms, statistics, model evaluation, and drift detection.

Responsabilités

• Design, develop, and deploy ML models for classification, prediction, anomaly detection, and automation.
• Build and maintain scalable data pipelines for training, evaluation, and inference.
• Optimize ML models for performance, scalability, reliability, and cost.
• Collaborate with cross-functional teams to integrate ML into core features.
• Experiment and evaluate models using quantitative metrics and A/B tests.

Connaissances

Python

PyTorch

TensorFlow

Scikit-learn

LLMs

Docker

Kubernetes

Vector databases

RAG

Agile teams

Formation

Bachelor's Degree

Outils

Docker

Kubernetes

LangChain

LangGraph

Spark

Ray

REST/gRPC

Description du poste

Omnissa, the AI-driven digital work platform, is hiring for an ML Engineer on the AI Platform Team. Location: Mountain View, CA or Atlanta, GA, hybrid work. You will design, deploy ML models, build data pipelines, and improve model performance at scale.

Requirements include 5+ years in ML engineering or data science, strong Python (PyTorch, TensorFlow, Scikit-learn), cloud experience (AWS/Azure/GCP), Docker/Kubernetes, and hands-on with LLMs and vector databases. Competitive USD salary.