Associate Machine Learning Engineer

Collaborate with data scientists to develop, train, and evaluate machine learning models.

Build and maintainMLOpspipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.

Leverage cloud platforms (AWS,Databricks) for ML model development, training, and deployment.

Develop solutions usingDevSecOpsframeworkthatare secure, scalable, reliable, and aligned with enterprise architecture standards.

Evaluate model performance usingappropriate metricsandoptimizemodels for accuracy and efficiency

Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software

Create andmaintaindocumentation on software architecture, design, deployment, disaster recovery, and operations

Identifyand resolve technical challenges effectively

Provide ongoing support and maintenance for applications, ensuringthattheyoperatesmoothly and efficiently

Analyze customer feedback and support data toidentifypain points and opportunities for improvement

Evaluate and recommend technologies and tools that best fit the solution requirements

Support operationalization of machine learning and GenAI models developed by data scientists and solution teams.

Assistin evaluating model and LLM performance using metrics related to reliability, efficiency, and response quality.

Support deployment and operation ofLLM‑basedworkflows, including prompt configurations,retrieval‑augmentedgeneration (RAG) pipelines, andagent‑basedautomations.

Assistwith monitoring AI and LLM systems for availability, latency, error rates, and quality degradation.

Support model, prompt, and pipeline versioning across development, test, and production environments.

Participate in incident triaging, root cause analysis, and rollback or mitigation activities for AI services.

Assistwith evaluation runs for LLM outputs, including grounding, reliability, and safety checks.

Follow established AI governance, security, and compliance standards whenoperatingAI and GenAI solutions.

Monitor AI and LLM endpoints for availability, latency, throughput, and error rates using enterprise monitoring tools.

Assistwith dashboards, alerts, runbooks, and operational documentation to support reliable AI system operations.