Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field
Advanced coursework or certifications in machine learning, deep learning, or NLP
Strong mathematical and statistical foundation
Experience Range
- 6–10 years of experience in AI/ML/Deep Learning model development
- 2-3 years Hands-on experience with LLMs, NLP, or speech/voice AI systems
- 3-5 years of experience deploying AI solutions in production environments
Primary (Must have skills)* - To be Screened by TA Team
- 5+ years of experience in Python, PyTorch, TensorFlow, or similar frameworks
- 3-5 years of experience designing, training, and fine-tuning large language models or AI models, speech/voice AI systems, Realtime voice pipeline
- 5 years of experience in cloud AI platforms (AWS Sagemaker, Azure ML, GCP AI)
- 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
- 2-3 years experience in Azure services — Azure AI Speech and Translator, Azure OpenAI, AI Search, plus Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights
Key technical skills :
- Design, develop, and deploy advanced AI models to meet business requirements
- Collaborate with data engineers, LLM Ops, and software teams for end-to-end solutions
- Evaluate model performance, fine-tune, and ensure scalability and reliability
- Research emerging AI/ML technologies and propose innovative solutions
- Mentor junior AI engineers and review code/models for best practices
Communication Skills:
- Clearly explain AI concepts and model behavior to technical and non-technical stakeholders
- Present complex model results in a concise and actionable manner
Interpersonal Skills:
- Collaborate effectively with cross-functional teams
- Provide constructive feedback and mentor junior team members
Problem-Solving and Analytical Thinking:
- 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
Task/ Work Updates
- Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
- Provides regular updates, proactive and due diligent to carry out responsibilities
Secondary Skills to be planned Post Hiring - Training Plan
- Advanced LLM techniques, prompt engineering, and fine-tuning strategies
- AI ethics, fairness, and responsible AI deployment
- Continuous learning on emerging AI frameworks and architectures
- LLMOps - layered evals (WER, entity F1, COMET), CI regression gates, tracing, cost-per-minute telemetry, model routing, and drift detection.