Transformative AI Developer

3 days ago

guntur, India beBeeArtificialIntelligence Full time

About us: We are a generative AI security platform that helps enterprises adopt AI responsibly, protecting AI workflows from data exposure, mitigating prompt vulnerabilities, and enforcing compliance policy in real time.Job Role:We are seeking an experienced Artificial Intelligence Developer to join our team.About the Job:The Artificial Intelligence Developer will be responsible for building production-grade services using Python/FastAPI with low latency, reliability, and observability.The developer will also work on model development, including training, fine-tuning, and evaluating AI models for classification, ranking, and anomaly detection.Additionally, the developer will profile and optimize inference (CPU/GPU), use batching/quantization/ONNX where useful, and keep latency within service level objectives (SLOs).The developer will build robust data/AI pipelines for training and inference (Python + SQL), with versioned datasets, deterministic preprocessing, and schema validation.Pipelines & data: Build robust data/AI pipelines for training and inference (Python + SQL), with versioned datasets, deterministic preprocessing, and schema validation.Experimentation: Design fair comparisons, select metrics (AUC/F1/PR-AUC/MAE), run ablations, and document decisions; automate tracking with MLflow/W&B (or similar).MLOps: Package and ship models/services using Docker and FastAPI; add health checks, logging/metrics, and continuous integration/continuous deployment (CI/CD).Monitoring: Set up drift/performance monitoring, alerting, and shadow→enforce rollouts with safe rollback paths.Collaboration & docs: Partner with backend/product teams to integrate models; write clear READMEs, design notes, and runbooks.Requirements:Experience in Data Science, Applied AI, or Large Language Model-based product development (2–3 years)Proficient in Python and comfortable writing SQL for data exploration or tagging workflowsSolid understanding of NLP concepts (Transformers, Attention, Tokenization, Fine-tuning)Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.), LangChain, and vector databases (FAISS, Pinecone, Chroma)Exposure to evaluation and red-teaming of LLMs for safety or robustnessBasic familiarity with Streamlit, Dash, or simple HTML/JS for building internal tools(Preferred) Experience deploying AI systems using Docker, FastAPI, or CI/CD pipelines in a startup or research setting

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