AI/ML Engineer

As an experienced AI/ML Engineer, you will be responsible for designing and implementing intelligent systems using large language models (LLMs) for observability and operational workflows. Your role will focus on building AI-driven solutions for anomaly detection, alert triage, and automated root cause analysis in production environments. Key Responsibilities: - LLM Development & Deployment - Design and deploy large language model solutions using Ollama, AWS Bedrock, or similar platforms - Implement agentic networks and multi-agent systems for complex operational workflows - Develop context-based prompt engineering strategies for production LLM applications - Fine-tune and optimize LLMs using LoRA (Low-Rank Adaptation) techniques - Integrate Model Context Protocol (MCP) for enhanced agent communication - Observability & Operations - Build AI-driven observability workflows for monitoring and operational intelligence - Design and implement intelligent alerting systems that reduce noise and improve signal quality - Develop automated alert triage mechanisms using ML-based classification - Create root cause analysis systems that leverage LLMs for faster incident resolution - Integrate LLM capabilities into existing operational pipelines and monitoring infrastructure - System Integration & Optimization - Develop robust APIs and integrations for LLM-powered features - Optimize model performance for latency-sensitive operational use cases - Implement monitoring and evaluation frameworks for LLM outputs - Build feedback loops to continuously improve model accuracy and relevance Required Qualifications: Technical Skills: - Strong proficiency in Python with experience in production-grade code - Hands-on experience with PyTorch, TensorFlow, LangChain, or similar frameworks - Practical experience deploying LLMs using platforms like Ollama, AWS Bedrock, OpenAI API, Anthropic Claude API, or similar - Proven ability to design effective prompts and context strategies - Git/GitHub proficiency AI/ML Experience: - 3+ years of experience in machine learning or AI engineering - Demonstrated experience working with large language models in production - Understanding of transformer architectures and attention mechanisms - Experience with model evaluation, testing, and performance optimization - Familiarity with vector databases and semantic search (Pinecone, Weaviate, ChromaDB, etc.) System Architecture: - Experience building scalable ML systems and APIs - Understanding of microservices architecture and containerization (Docker, Kubernetes) - Familiarity with cloud platforms (AWS, GCP, or Azure) - Knowledge of CI/CD pipelines for ML models Additional Details: The company provides benefits such as food, health insurance, life insurance, paid sick time, and paid time off. Educational Background: - Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field - Equivalent practical experience will be considered - PhD in AI/ML or related field is a plus What You'll Work On: Near-Term Projects: - Deploy LLM-powered alert triage system to reduce on-call burden - Build intelligent incident summarization using context-aware prompts - Implement anomaly detection for production metrics using ML models - Create automated root cause analysis workflows Long-Term Vision: - Develop self-healing systems that use LLMs for autonomous remediation - Build predictive models for proactive issue detection - Create natural language interfaces for operational queries - Design multi-agent systems for complex operational decision-making Job Type: Full-time,