Eryk I.
Senior Machine Learning Engineer
Experience
Senior Machine Learning Engineer
Salento
- Led the design and deployment of a RAG-based system using GPT-4 and LangChain, improving response accuracy and system efficiency in real-time chatbot applications.
- Optimized the performance of NLP models integrated with vector search engines, enhancing search precision in document retrieval tasks for global clients.
- Implemented distributed training for LLMs, reducing model training times and improving scalability for large datasets.
- Developed and managed automated pipelines for model fine-tuning, allowing for faster iteration cycles and improved model accuracy in production.
- Worked closely with product teams to align business needs with machine learning solutions, improving client satisfaction and operational efficiency.
Senior Machine Learning Engineer
IBM
- Developed and deployed a RAG-based system using Hugging Face Transformers, improving document retrieval and summarization accuracy for enterprise applications.
- Built and optimized machine learning pipelines on AWS/GCP, improving model training efficiency and reducing operational costs through better cloud resource management.
- Fine-tuned large language models like GPT-3 for domain-specific applications, improving the relevancy of generated content for clients.
- Integrated LangChain with vector search engines (Pinecone, FAISS) for more efficient query processing in enterprise-level applications.
- Collaborated with DevOps teams to containerize machine learning models, enabling scalable deployments using Docker and Kubernetes.
- Mentored junior engineers, sharing knowledge on best practices for NLP model training and deployment.
- Conducted performance evaluations of existing models, identifying and implementing strategies that enhanced both accuracy and processing time.
Machine Learning Engineer
Luminance
- Fine-tuned BERT-based models for text classification tasks, enhancing the model’s performance on specific client datasets.
- Built and deployed NLP pipelines for automatic text summarization, significantly reducing the time required for content review.
- Worked with cross-functional teams to integrate machine learning models into production, ensuring a smooth scaling process for client-facing services.
- Led the implementation of cloud-based services for NLP model deployment, optimizing both latency and scalability for large datasets.
Software Engineer
Tooploox
- Fine-tuned NLP models for text classification tasks, resulting in improved accuracy and faster processing for internal tools.
- Designed and implemented data preprocessing pipelines, significantly reducing model training times and streamlining the deployment process.
Summary
A Senior Machine Learning Engineer with over 9 years of experience in Natural Language Processing and Large Language Models. I have a strong track record of designing, deploying, and fine-tuning advanced machine learning models, particularly in NLP and LLM applications. With a deep focus on building production-ready systems, I have successfully led initiatives across various industries to optimize performance and scale NLP solutions. My expertise spans the full machine learning lifecycle, from model development to deployment in cloud environments, utilizing technologies like PyTorch, Hugging Face, and RAG-based architectures. I have worked at tech firms and consulted for startups, providing impactful AI solutions that address real-world problems.
Languages
Education
University of London
Master of Science in Computer Science · Computer Science · London, United Kingdom
Heriot-Watt University
Bachelor of Science in Computer Science · Computer Science · Edinburgh, United Kingdom
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