Machine Learning Engineer ML Ops

As a Machine Learning Engineer (Support & Ops focus) at Aera Technology, your primary responsibility will be to ensure that the AI-powered decision systems run reliably at scale. Your role will involve less model building from scratch and more focus on maintaining production AI systems in a healthy, observable, and performant state to enable Data Science teams to deliver efficiently. This position also serves as a stepping stone towards ML feature development, offering exposure to advanced ML tooling and collaboration with cross-functional teams. **Key Responsibilities:**

• Monitor, troubleshoot, and maintain ML pipelines and services in production to ensure high availability and minimal downtime. - Operationalize ML/LLM models in collaboration with Data Scientists and Engineers, from development through deployment. - Develop and maintain observability tools for tracking data quality, model performance, drift detection, and inference metrics. - Support LLM and Agentic AI features in production with a focus on stability, optimization, and seamless integration. - Enhance internal ML tooling for faster experimentation, deployment, and feature integration. - Collaborate with Product teams to implement new ML-driven features and enhance existing ones. - Improve CI/CD workflows for ML code, data pipelines, and models in collaboration with DevOps. - Optimize resource usage and costs for large-scale model hosting and inference. - Document workflows, troubleshooting guides, and best practices for ML systems support. **Qualifications Required:**
• B.E./B.Tech in Computer Science, Engineering, or related field. - 3-5 years of experience in software engineering, ML Ops, or ML platform support. - Strong Python skills with experience in production-grade code and automation. Familiarity with ML pipeline orchestration tools like Airflow, Prefect, Kubeflow, or similar. - Proficiency in containerized microservices (Docker, Kubernetes), CI/CD pipelines, and monitoring tools like Prometheus, Grafana, ELK, Sentry, or equivalent. - Understanding of model packaging and serving frameworks such as FastAPI, TorchServe, Triton Inference Server, Hugging Face Inference API. - Strong collaboration skills with cross-functional teams. As an Aeranaut at Aera Technology, you will be part of a series D startup established in 2017, headquartered in Mountain View, California, with global teams in multiple locations. Apart from a competitive salary and company stock options, you can benefit from comprehensive medical insurance, paid time off, maternity leave, access to professional development courses, and a flexible working environment to ensure a healthy work-life balance. If you are passionate about building a sustainable, intelligent, and efficient world, Aera Technology welcomes you to join their innovative team. As a Machine Learning Engineer (Support & Ops focus) at Aera Technology, your primary responsibility will be to ensure that the AI-powered decision systems run reliably at scale. Your role will involve less model building from scratch and more focus on maintaining production AI systems in a healthy, observable, and performant state to enable Data Science teams to deliver efficiently. This position also serves as a stepping stone towards ML feature development, offering exposure to advanced ML tooling and collaboration with cross-functional teams. **Key Responsibilities:**