MLOps Engineer

Skills/Experience 6 10 years of experience in AI/ML/Deep Learning model development; 5 years of experience in Cloud AI platforms (AWS SageMaker / Azure ML / Google Cloud Platform AI) 2-3 years hands-on experience with LLMs, NLP, or speech/voice AI systems and deploying AI solutions in production environments 3-5 years of experience designing, training, and fine-tuning LLMs or AI models, Speech/Voice AI systems, Realtime voice pipeline 2+ years of experience in Agentic AI frameworks such as LangChain, LangGraph, A2A, MCP, and Multi agent orchestration 2-3 years of experience Familiarity with model evaluation metrics, bias detection, and optimization 5 years of experience in integrating AI models into applications via APIs or pipelines 3+ years of experience in Python, PyTorch, TensorFlow, or similar frameworks 2-3 years in Azure services - Azure AI Speech & Translator, Azure OpenAI, AI Search, plus Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field Strong mathematical and statistical foundation; Preferred - Advanced coursework or certifications in ML, DL, or NLP Secondary / Preferred Skills Advanced LLM techniques, prompt engineering, and fine-tuning strategies; Continuous learning on emerging AI frameworks and architectures; AI ethics, fairness, and responsible AI deployment; LLMOps - layered evals (WER, entity F1, COMET), CI regression gates, tracing, cost-per-minute telemetry, model routing, and drift detection.

Role / Job Description Design, develop, and deploy advanced AI models to meet business requirements; Research emerging AI/ML technologies and propose innovative solutions Evaluate model performance, fine-tune, and ensure scalability and reliability; Collaborate with data engineers, LLM Ops, and software teams for end-to-end solutions Clearly explain AI concepts and model behavior to technical and non-technical stakeholders; Mentor junior AI engineers and review code/models for best practices Identify bottlenecks in model performance and propose solutions; Troubleshoot deployment or integration challenges proactively Analyze data patterns and model outputs to derive insights; Apply structured thinking to optimize AI workflows and pipelines Present complex model results in a concise and actionable manner; Collaborate effectively with cross-functional teams Provide constructive feedback and mentor junior team members; Problem-Solving and Analytical Thinking Experience in Agile/Scrum projects with exposure to tools like Jira/Azure DevOps Provides regular updates, proactive and due diligent to carry out responsibilities

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