Artificial Intelligence

• Leadership & Management
• - Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
• - Drive the roadmap for machine learning projects aligned with business goals;
• - Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery.
• Machine Learning & LLM Expertise
• - Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
• - Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
• - Stay ahead of advancements in LLMs and apply emerging technologies;
• - Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML.
• AWS Cloud Expertise
• - Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
• - Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
• - Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.
• Technical Execution
• - Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
• - Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
• - Debug, troubleshoot, and optimize production ML models for performance.
• Team Development & Communication
• - Conduct regular code reviews and ensure engineering standards are upheld;
• - Facilitate professional growth and learning for the team through continuous feedback and guidance;
• - Communicate progress, challenges, and solutions to stakeholders and senior leadership.

AI/ML Tech Lead, LLMs, AWS

Specjalista/ka ds. sprzedaży, AI

AI/ML TechLead, LLMs, AWS

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