À propos
Austin TX 78744
Minimum Years of Experience, Skills, and Qualifications
Core Technical (Foundational):
" Python
1-2 years of hands-on experience through professional work, internships, or substantial projects
" AI/ML Fundamentals
Experience building and evaluating ML models beyond coursework (projects, internships, early production exposure)
" Cloud Platforms
Familiarity with at least one major cloud platform (AWS, Azure, GCP, or OCI); production depth not required
" DevOps Basics
Introductory experience with Docker and basic CI/CD concepts
" Databases
Basic experience with SQL and exposure to NoSQL or vector databases
" Scripting
Working knowledge of Bash or PowerShell for simple automation
ML Domains (Experience or strong interest in 1-2 areas):
" NLP/LLMs: Coursework or project experience with transformers, prompt engineering, or LLM applications
" Time Series: Introductory experience with forecasting or anomaly detection
" Recommender Systems: Academic or project exposure to personalization or ranking models
" MLOps Tools: Familiarity with MLflow, Airflow, or similar tools is a plus but not required
Preferred Skills and Qualifications
Exposure to CI/CD tools such as GitHub Actions or Azure DevOps
Basic computer vision experience through projects or labs
Familiarity with PyTorch or TensorFlow
Interest in edge deployment, streaming data, or real-time ML systems
Open-source contributions, coursework projects, or technical blogs
Our Stack:
Core: Python | PyTorch/TensorFlow | Scikit-learn | FastAPI/Flask | Git | Bash/PowerShell
ML/AI Tools: MLflow | Airflow/Kubeflow | Azure AI | AWS SageMaker/Bedrock | GCP Vertex AI | OCI AI Services
Infrastructure: Docker | Kubernetes | AWS/Azure/GCP/OCI | PostgreSQL | Azure DevOps | GitHub Actions
Compétences linguistiques
- English
Avis aux utilisateurs
Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.