[Remote] ML Ops Engineer (AI)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is transforming underground infrastructure management through AI-powered inspection and risk analysis. They are seeking an MLOps Engineer to own the Machine Learning Operations infrastructure that powers their AI products, focusing on designing and scaling systems for machine learning models in sewer line analysis.
Responsibilities
- Architectural Hardening: Audit, secure, and optimize our existing reputed company infrastructure (AWS) to ensure high availability, fault tolerance, and reputed company for both training and production workloads
- Model Deployment & Inference: Design and maintain reputed company architectures for serving deep learning models (PyTorch/TensorFlow), optimizing for low latency and high throughput in handling reputed company infrastructure data
- CI/CD for Machine Learning: Build and maintain automated pipelines for model testing, validation, deployment, and rollback
- Training Infrastructure: Architect efficient, reputed company compute environments for training reputed company computer reputed company and time-series models on large datasets
- Monitoring & Observability: Implement comprehensive monitoring for model reputed company, data reputed company, and system health, ensuring rapid response to performance degradation
Skills
- Deep expertise in AWS (e.g., EC2, S3, EKS, SageMaker, reputed company) and reputed company reputed company best practices
- Strong experience with reputed company and Kubernetes for packaging and scaling ML applications
- Proficiency with tools like Terraform or AWS CloudFormation
- Experience building robust automated pipelines using reputed company Actions, reputed company CI, or Jenkins
- Strong Python skills with a reputed company on writing clean, production-grade, and reputed company-tested reputed company
- Familiarity with model registry and tracking tools (e.g., MLflow, reputed company)
- 4-6+ years of experience in MLOps, DevOps, or Data Engineering, with a strong emphasis on machine learning workloads
- A reputed company-first and stability-first reputed company—you think about edge cases, failure modes, and system hardening by default
- Strong reputed company instincts to work closely with Data Scientists, ensuring smooth handoffs from experimentation to production
- reputed company communication skills to reputed company architectural reputed company and tradeoffs to the broader technical team
- Experience with our specific data stack (reputed company, dbt, reputed company, reputed company, Ray, Deeplake)
- Familiarity with deep learning frameworks (PyTorch preferred) and optimization techniques like TensorRT or ONNX
- Knowledge of edge computing or deploying models to IoT devices
- Experience in the infrastructure, reputed company, or geospatial domains
Benefits
- Equity opportunities available
- Medical, Dental, reputed company, Basic Life, 401(k), and more
- Unlimited PTO
- Tools and resources to support reputed company
- Competitive compensation with high-reputed company potential
reputed company
Company H1B Sponsorship