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Tech Lead
Louisville, KY
Description
Location- Onsite
Lead Machine Learning Engineer (MLOps & LMOps)
This position designs, builds, tests, and delivers production grade AI systems, with a specific focus on language model operations (LMOps)รขโฌยฟthe deployment, monitoring, and scaling of both small and large language models. This position works in collaboration with Architecture, Engineering, and Data Science teams to operationalize intelligent systems that power AI and data science products. This position is responsible for implementing end to end pipelines for language models and traditional ML models, integrating CI/CD workflows, model monitoring, and infrastructure as code practices. The role contributes to the continuous improvement of AI infrastructure and deployment reliability across cloud native environments.
You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business.
o Performs detailed design of complex applications and complex architecture components
o May lead a small group of developers in configuring, programming, and testing
o Fixes medium to complex defects and resolves performance problems
o Accountable for service commitments at the individual request level for in scope applications
o Monitors, tracks, and participates ticket resolution for assigned tickets
o Manages code reviews and mentors other developers
Tech Lead
Louisville, KY
Description
Onsite role
Machine Learning Engineer รขโฌยฟ MLOps, VertexAI, LLMs, GenAI, ML Model Management
We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems.
You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business.
o Under general supervision, works on software development assignments within a specific software functional area or product line
o Conducts unit testing on the module
o Involved in execution and reporting for system integration testing and regression testing