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AI/ML Lead Engineer

MetaSense, Inc.United States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
Stakeholder ManagementAWSMLOpsNLPScikit-learnDeep LearningGoogle CloudKerasLLMPyTorchPythonTensorFlowGenerative AIAzureMachine LearningPrompt EngineeringLangChainLangGraphRAG

Job description

Title: AI/ML Lead Engineer

Location: Remote
Duration: Long Term
Interview Mode: Video
Job Summary
We are looking for an experienced AI/ML Lead Engineer to lead the design, development, and deployment of enterprise-grade Artificial Intelligence and Machine Learning solutions. The ideal candidate should have a strong foundation in traditional Machine Learning, Deep Learning, Generative AI, LLMs, and Agentic AI, along with hands-on development and technical leadership experience.
Key Responsibilities
  • Lead the architecture, design, development, and implementation of AI/ML solutions.
  • Drive end-to-end Machine Learning initiatives, including data preparation, model development, training, validation, and deployment.
  • Design and develop Generative AI applications, AI agents, and multi-agent systems.
  • Build and optimize LLM-based applications using RAG, prompt engineering, embeddings, and vector databases.
  • Develop predictive models, classification, regression, clustering, and forecasting solutions.
  • Work with Deep Learning, NLP, neural networks, and advanced ML algorithms.
  • Leverage frameworks such as LangChain, LangGraph, and LlamaIndex for AI application development.
  • Integrate AI/ML models with enterprise applications, APIs, and cloud platforms.
  • Evaluate and optimize model performance, accuracy, scalability, and cost efficiency.
  • Establish MLOps practices for model deployment, monitoring, versioning, and continuous improvement.
  • Lead technical discussions, architecture reviews, and mentor AI/ML engineering teams.
  • Collaborate with business stakeholders, architects, and product teams to deliver AI-driven solutions.
Required Skills
  • Strong programming experience in Python and AI/ML engineering.
  • Strong foundation in Machine Learning, Deep Learning, and Statistical Modeling.
  • Hands-on experience with ML algorithms, predictive modeling, classification, regression, and clustering.
  • Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.
  • Strong experience in Generative AI, LLMs, and Agentic AI.
  • Experience building AI agents and multi-agent architectures.
  • Knowledge of RAG, embeddings, vector databases, and prompt engineering.
  • Experience with LangChain, LangGraph, or similar AI frameworks.
  • Exposure to OpenAI, Azure OpenAI, Anthropic Claude, or other LLM platforms.
  • Experience with MLOps, model deployment, monitoring, and model lifecycle management.
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Strong technical leadership and stakeholder management skills.

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