AI Engineer
- Fine-tune and deploy open-source general purpose LLMs and code-generation models (e.g. Llama 4, qwen2.5) using PEFT, LoRA, QLoRA, instruction tuning, RLHF, etc..
- Design GenAI applications with agentic capabilities—autonomous, goal-driven agents that can plan, reason, and execute multi-step workflows with minimal human input.
- Implement function calling in workflows, enabling models to invoke external tools, APIs, databases, and services to perform actions or access real-time data.
- Build agentic RAG pipelines, where LLMs coordinate data retrieval and reasoning dynamically via retrieval-augmented generation.
- Create and maintain scalable pipelines, including data ingestion, labeling, feature engineering, vector DB management, and MLOps frameworks (MLflow, Kubeflow).
- Containerize applications using Docker, Kubernetes.
- Optimize and monitor model performance, including latency, drift, bias, privacy, and security compliance.
- Collaborate cross-functionally, mediating between data, product, and engineering teams to translate requirements into agentic GenAI solutions.
- Stay current with research trends like agentic RL frameworks (e.g., ARTIST), multi-agent orchestration, MCP, secure function calling.
- B.S or M.S. in Computer Science, Data Science, ML/AI or equivalent.
- 3-5 years building and deploying AI/ML solutions with demonstrable production experience.
- Extensive experience fine-tuning LLMs and code models with advanced techniques (PEFT/LoRA/QLoRa/RLHF).
- Proven track record designing or delivering agentic GenAI applications—function calling, autonomous workflows, RAG pipelines.
- Proficient in Python, PyTorch/TensorFlow, Hugging Face, LangChain, LangGraph or similar frameworks.
- Experience in Document and Image Analysis and extracting insights from unstructured data, including text documents and images.
- Strong infrastructure skills: Docker, Kubernetes, CI/CD, MLOps tooling.
- Sharp analytical mindset for system optimization, error mitigation, and security best practices.
- Excellent problem-solving and ability to translate business needs into technical design.
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