AI Systems Developer
1 week ago
Machine Learning EngineerAbout our team:We develop and deploy large-scale AI systems to help enterprises adopt AI responsibly. Our goal is to protect AI workflows from data exposure, mitigate prompt vulnerabilities, and enforce compliance policy in real time.Main Responsibilities:We build production-grade services in the request/response path using Python/FastAPI with low latency, reliability, and observability.We train, fine-tune, and evaluate ML models for classification, ranking, and anomaly detection; improve accuracy with solid feature engineering and error analysis.We profile and optimize inference (CPU/GPU), use batching/quantization/ONNX where useful, and keep latency within service level objectives (SLOs).We build robust data/ML pipelines for training and inference (Python + SQL), with versioned datasets, deterministic preprocessing, and schema validation.We design fair comparisons, select metrics (AUC/F1/PR-AUC/MAE), run ablations, and document decisions; automate tracking with MLflow/W&B (or similar).We package and ship models/services using Docker and FastAPI; add health checks, logging/metrics, and CI/CD (GitHub Actions/Jenkins).We set up drift/performance monitoring, alerting, and shadow→enforce rollouts with safe rollback paths.We partner with backend/product teams to integrate models; write clear READMEs, design notes, and runbooks.Required Qualifications:2–3 years of experience in Data Science, Applied ML, or LLM-based product development.Proficient in Python and comfortable writing SQL for data exploration or tagging workflows.Solid 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 robustness.Basic familiarity with Streamlit, Dash, or simple HTML/JS for building internal tools.(Preferred) Experience deploying ML systems using Docker, FastAPI, or CI/CD pipelines in a startup or research setting.The benefits of working with us:We invest in your growth and development as an AI professional.We offer a collaborative and dynamic work environment that encourages creativity and innovation.We provide opportunities to work on challenging projects and contribute to cutting-edge AI research.We prioritize diversity, equity, and inclusion in all aspects of our organization.What we look for in candidates:A strong background in machine learning and deep learning.Experience with large-scale AI system development and deployment.Excellent communication and collaboration skills.A passion for staying up-to-date with the latest AI trends and advancements.
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