Applied AI Researcher - MLOps
2 days ago
Ansible
AWS
Azure
Chef
Cloud
Django
Docker
Flask
Google Cloud Platform
Grafana
GRPC
JavaScript
Keras
Kubernetes
MongoDB
MySQL
Postgres
Prometheus
Puppet
Python
PyTorch
RabbitMQ
Redis
Spring
Spring Boot
SpringBoot
Tensorflow
Terraform
Go
Description
• About us: At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. • Job Description: Articul8 AI is seeking an exceptional Applied AI Researcher-MLOps to shape the future of Generative Artificial Intelligence (GenAI). • Responsibilities: Design, develop, and maintain pipelines for data and models. • Model Deployment: Manage deployment pipelines for AI/ML models. • Infrastructure Management: Maintain infrastructure for deploying and scaling AI/ML models. • Monitoring: Implement systems to track model performance. • Collaboration: Work with cross-functional teams to innovate and maintain product technology leadership. • Preferred Qualifications: 3+ years as an MLOps Engineer and experience in developing tools for data preprocessing and model training.
Requirements
• Education: BSc or MSc degree in Computer Science, Data Science/Machine Learning, or a related field. • Professional experience: 2+ years in MLOps, DevOps, or related roles deploying machine learning models in production environment. • Core technical skills: • Cloud Platforms: AWS, Azure, GCP • Development: Python, PyTorch, Keras, Julia, Go, CI/CD pipelines, and version control. • ML Platforms: MLflow, Kubeflow, TFX (TensorFlow Extended), serving platforms (gRPC, ONNX, JIT) • Monitoring: Prometheus, Grafana, ELK Stack • Container/Orchestration: Docker, Kubernetes, Docker Swarm, RabbitMQ. • Theoretical foundation: deep learning, traditional machine learning, probability and statistics, natural language processing, computer vision, data wrangling and preparation, and model evaluation and interpretation. • Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.
Benefits
• Professional development opportunities, including training and mentorship programs • Flexible work arrangements, including remote work options • Access to the latest technologies and tools • Regular social events and team-building activities • A supportive and inclusive work environment
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