Machine Learning Engineer

• AI Solution Development: Design and deploy AI/ML solutions with a focus on generative models (LLMs).
• Orchestration and Agents: Implement and optimize complex workflows using frameworks such as LangChain and LangGraph for agent and model orchestration.
• Data and Model Pipelines: Build and maintain efficient data pipelines for ingestion, preprocessing, training, and model deployment.
• Integration and Scalability: Integrate AI models with APIs, microservices, and enterprise systems, ensuring scalable, high-performing solutions.
• Strategic Collaboration: Actively collaborate with business areas (marketing, sales, operations) to identify and capitalize on AI-driven innovation opportunities.
• Quality and Ethics: Ensure security, compliance, and ethical best practices in all AI solutions developed.
• LLM Optimization: Apply advanced prompt engineering and fine-tuning techniques to maximize LLM performance.
• Monitoring: Monitor and optimize production models for accuracy, latency, and cost.
• Documentation: Document architectures, workflows, and best practices to promote reuse and standardization.

Engineer, Machine Learning, Generative AI

Senior Machine Learning Engineer

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AI Developer

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Mid-level Machine Learning Engineer