Qualifications
- Masters degree preferred
- Experience having led multiple projects leveraging LLMs, GenAI and Prompt Engineering Exposure to real-world MLOps deploying models into production adding features to products
- Knowledge of working in a cloud environment
- 5+ Years of Experience
- Strong understanding of LLMs, GenAI, Prompt Engineering and Copilot
Career Level - IC3
Responsibilities
- The ML Engineer is expected to fully own the services that are built with the ML Scientists. This cuts across scalability, availability, having the metrics in place, alarms/alerts in place – and be responsible for the latency of the services
- Cloud Administration: administration of VMs and the cloud admin stuff including patching VMs, upgrading packages, working with endpoints, load balancing etc.; Production support of models managing incidents related to the models & data
- Setup CI/CD pipelines for the ML scientists and own the production pipeline around pushing things to prod; Setup and own MLOps environment around cloud
- Data quality checks & onboarding the data on to the cloud for modeling purposes
- Build extensible solutions around drift checks (model drift, data drift, concept drift), production quality code and impact assessment
- These roles should have a ML Sciences understanding as well
- Prompt Engineering, FT work, Evaluation, Data
- End-end AI Solution architecture, latency tradeoffs, LLM Inference Optimization, Control Plane, Data Plate, Platform Engineering
- Comfort in Python and Java is highly desirable