Machine Learning Operations (MLOps) Engineer

LVIS; Palo Alto (CA); On-site; USD 160,000; Full time

Job summary

LVIS is seeking a Machine Learning Operations (MLOps) Engineer to join our innovative team in Palo Alto. In this role, you will be responsible for developing and maintaining scalable APIs for machine learning models, optimizing workloads in the AWS cloud, and ensuring operational stability of ML models. The ideal candidate will have a strong background in MLOps, three or more years of experience in the field, and a passion for advancing neurology healthcare through cutting-edge technology.

Qualifications

• 3+ years of experience in MLOps or ML Engineering.
• Experience with ML-related programming languages and frameworks (Python, PyTorch, TensorFlow).
• Hands-on experience with AWS and GPU-based model training.

Responsibilities

• Develop and maintain APIs for deploying machine learning models.
• Optimize machine learning workloads on AWS for performance and cost efficiency.
• Design and implement tracking systems for model performance.

Skills

Machine Learning

API Development

Data Processing

Cloud Optimization

Container Management

Education

Bachelor's degree in Computer Science, Data Science, AI, or related fields

Tools

AWS

Kubernetes

Docker

MLflow

Job description

Machine Learning Operations (MLOps) Engineer

Machine Learning Operations (MLOps) Engineer

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Company Description

LVIS, through our advanced brain network analysis tools, provides Live Visualization to innovate how neurological diseases are diagnosed and treated. LVIS is a leader in cutting edge neural information analysis technologies that can decode brain networks and find cures for neurological diseases. LVIS owns patented technologies and our team includes leaders with strong expertise in neuroscience and engineering from Stanford University. LVIS has been selected to be a member of the Stanford StartX community and the NVIDIA inception program. We have an international team with our headquarter located in Palo Alto, California, USA and we have an office in Gangnam, Seoul, South Korea. We are looking for talented individuals to join us in transforming the neurology health care industry.

Company Description

LVIS, through our advanced brain network analysis tools, provides Live Visualization to innovate how neurological diseases are diagnosed and treated. LVIS is a leader in cutting edge neural information analysis technologies that can decode brain networks and find cures for neurological diseases. LVIS owns patented technologies and our team includes leaders with strong expertise in neuroscience and engineering from Stanford University. LVIS has been selected to be a member of the Stanford StartX community and the NVIDIA inception program. We have an international team with our headquarter located in Palo Alto, California, USA and we have an office in Gangnam, Seoul, South Korea. We are looking for talented individuals to join us in transforming the neurology health care industry.

LVIS provides an environment where everyone is expected to grow with the company. We are looking for self motivated team members who will be at the leading edge of technology.

Responsibilities

• Develop and maintain APIs: Deploy machine learning models as APIs and build scalable API services
• Optimize machine learning workloads on the cloud: Improve performance and cost-efficiency of ML models on AWS
• Ensure operational stability: Design and implement real-time data processing, logging, monitoring, and model performance tracking systems
• Deploy ML models in real-world environments: Ensure reliable deployment and management of ML models and data drift in production
• Utilize GPU and GPU clusters: Configure and optimize GPU-based environments for model training and inference (on Cloud and on-premise)
• Build MLOps pipelines on AWS and Kubernetes: Deploy and manage containerized ML workflows in Kubernetes environments
  
  
  

Basic Qualifications

• Bachelor's degree or higher in Computer Science, Data Science, AI, or related fields
• 3+ years of experience in MLOps or ML Engineering
• Experience of ML related programming languages and frameworks (Python, PyTorch, TensorFlow, etc.)
• Experience deploying and managing ML models using tools like MLflow, TensorFlow Serving, or TorchServe
• Hands-on experience with AWS
• Proficiency in managing and orchestrating containers using Kubernetes and Docker
• Experience with GPU-based model training and optimization
• Experience building large-scale data processing pipelines (Airflow, Kafka, etc.)
  
  
  

Preferred Qualifications

• Hands-on experience with CI/CD pipelines (Jenkins, ArgoCD, etc.)
• Experience in large-scale AI model serving
• Knowledge of real-time data streaming and batch processing
• Preferably DevOps experience along with MLOps

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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