Advanced AI Developer

2 days ago

Mumbai, Maharashtra, India beBeeMachineLearning Full time US$ 2,00,000 - US$ 2,40,000
Machine Learning Engineer

We are seeking a seasoned Machine Learning Engineer to develop intelligent systems that enhance our cloud security platform.

  • Leverage your expertise in ML/AI to build production-ready systems that streamline alert prioritization, classification, and contextualization.
  • Work at the intersection of LLM-driven automation, workflow orchestration, and classical ML models to optimize system performance.
About the Role

This key position allows you to influence the development of agentic AI systems, workflow automation, and recommendation engines within our platform.

You will collaborate closely with data scientists, ML engineers, security researchers, and software teams to build end-to-end solutions.

Key Responsibilities
  1. Integrate LLMs into existing systems and develop agentic workflows for investigation, classification, and automated response by applying techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning.
  2. Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification using both classical models (AR, ARIMA, SARIMA) and modern architectures (XGBoost, LSTM, DeepAR, Temporal Fusion Transformer).
  3. Collect, preprocess, and transform structured and unstructured data, including logs, text, and access patterns, then engineer features to maximize model interpretability and performance.
  4. Train and evaluate models using rigorous metrics (precision, recall, AUC, F1, etc.) and optimize hyperparameters before deploying ML and LLM models at scale into production with strong monitoring, drift detection, and observability.
Requirements
  • Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
  • 5+ years of experience in ML/AI, with at least 3 years deploying production-grade systems.
  • Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
  • Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face, LangChain, LlamaIndex).
  • Hands-on experience building workflow automation with LLMs and integrating them into applications.
  • Solid programming skills in Python (PyTorch, TensorFlow, scikit-learn).
  • Knowledge of NLP tasks such as text classification, summarization, and semantic search.
  • Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps best practices.
  • Strong problem-solving, analytical, and communication skills.
  • The ability to thrive in a fast-paced, evolving startup environment.

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