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AI Implementation Engineer - Toptal
Summary
We are looking for an AI Engineer to help design, build, and improve AI-powered applications and agentic systems. This role is broad and best suited for engineers who have hands-on experience working with LLMs, RAG pipelines, AI agents, and modern AI orchestration frameworks
General Information:
The engineer will work on building production-ready AI solutions that combine LLMs, tools, retrieval systems, workflows, and integrations. The ideal candidate is comfortable moving from experimentation to implementation and can make practical engineering decisions around reliability, scalability, and maintainability.
Tasks and deliverables
Required Experience:
Engagement highlights:
Job ID: 150575905
Skills:
Machine Learning, Cnn, Data Cleansing, Clustering, Deep Learning, MLops, Artificial Neural Networks, Decision Trees, Azure, Python, AWS, LSTM, model validation, Data Workflows, Support Vector Machines, Retrieval-Augmented Generation, Feature Selection, YOLO, Quadratic Programming, genetic algorithms, Large Language Models, Exploratory Analytics
Skills:
Machine Learning, Data Structures, Cyber Security, Data Science, Algorithms, Frameworks, System Design, Python, Problem-solving, Feature Engineering, Computer Science, Model Evaluation, R, ML Libraries, Experimental Design
Skills:
Python, LangChain, LLM architecture, Transformers, LLM APIs, attention mechanisms, open-source LLMs, cloud-based AI solutions, API integration tools
Skills:
Apis, Git, Rest Apis, Python, Asynchronous processing, LLMs, NoSQL databases, Cloud environment, information extraction, Document Processing, Quality metrics, Evaluation datasets, cost tracking, Relational Databases, Error handling, Regression tests, Model-output validation, Backend services, Monitoring
Skills:
MLops, DevSecOps, Docker, Kubernetes, LLMs, cloud platforms, AI-native systems, modern AI architecture