
Staff Machine Learning Engineer
Omnissa
full-time
Posted on:
Location Type: Hybrid
Location: Mountain View • California • United States
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Salary
💰 $162,512 - $342,750 per year
Job Level
About the role
- Design, develop, and deploy machine learning models for classification, prediction, anomaly detection, and intelligent automation.
- Build and maintain scalable data pipelines for model training, evaluation, and real time /batch inference.
- Optimize ML models and pipelines for performance, scalability, reliability, and cost efficiency.
- Collaborate with cross functional teams to integrate ML solutions into core platform features and services.
- Conduct model experimentation, evaluation, and iteration using quantitative metrics and A/B testing as needed.
- Implement model observability, monitoring, and drift detection to ensure production reliability.
- Stay current with advancements in machine learning, AI, and LLM technologies, and apply them to product use cases.
Requirements
- 5+ years of experience in machine learning engineering or data science roles
- Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit learn)
- Experience building and operating data processing workflows (batch or streaming) and working with cloud platforms (AWS, Azure, or GCP)
- Solid understanding of machine learning algorithms, statistics, and model evaluation techniques
- Familiarity with containerization and orchestration technologies (Docker, Kubernetes)
- Hands on experience with Large Language Models (LLMs), including fine tuning, prompt engineering, and deployment
- Knowledge of text embedding models, and vector databases for Retrieval Augmented Generation (RAG) systems
- Strong problem-solving skills and the ability to collaborate effectively in Agile teams
- Highly motivated, adaptable, and eager to learn new technologies.
Benefits
- employee ownership
- health insurance
- 401k with matching contributions
- disability insurance
- paid-time off
- growth opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdata sciencePythonPyTorchTensorFlowScikit learndata processing workflowsmachine learning algorithmsmodel evaluation techniquesLarge Language Models
Soft Skills
problem-solvingcollaborationadaptabilityeagerness to learn