Machine Learning Engineer - AI/ML/LLM and MLOPS Engineer

Lead with AI/ML/LLM and MLOPS Engineer

Remote (Preferred from Austin, TX)

Contract

The vendor will support the development, deployment, and maintenance of machine learning pipelines, AI-powered applications, and self-hosted large language model (LLM) inferencing infrastructure.

The team will take proof-of-concepts and prototypes developed by Apple engineers and scale them into production-grade systems, adhering to best practices in software development, MLOps, and cloud infrastructure management.

Technology stack that team will be working on (MLOPS, ICEberg, AWS and front end Lightweight NextJS are important)

Tech stack details:-
• Backend: Python (Django, FastAPI)
• Unit/integration testing (pytest)
• Asynchronous job scheduling (Celery)
• Adherence to PEP8 and PEP257 coding standards
• Frontend: ReactJS (Next.js)
• Machine Learning:
• Python ML & DS ecosystem (PyTorch, XGBoost, scikit-learn, pandas, numpy)
• Model interpretability & explainability frameworks (SHAP)
• ML pipelines & workflow automation (MLflow, Airflow)
• Infrastructure: AWS (EC2, S3, EKS, SageMaker)
• Infrastructure as Code (IaC) using Terraform and Ansible
• Proper IAM role-based access controls
• Network security best practices (VPC, security groups, private subnets)
• MLOps:
• Model training, monitoring, & deployment (MLflow, AWS SageMaker, AWS Airflow)
• Data labeling & versioning (Label Studio, DVC
• CI/CD & Monitoring:
• Automated linting, test & deployment: Jenkins
• Telemetry & Monitoring: Prometheus, Grafana, AWS CloudWatch
• Containerization & Orchestration: Docker, Kubernetes, Helm
• Additional technologies as needed