Hire Expert Large Language Models Developers
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Featured Large Language Models Developers
Saad Siddiqui
I'm a Lead Data Scientist and Machine Learning Engineer with 10+ years of experience building and deploying AI/ML systems across telecom, healthcare, and finance. I specialize in LLM applications, deep learning, NLP, and end-to-end ML pipelines. At Afiniti, I led the development of a RAG-based ChatGPT platform, agentic video generation workflows, and AI-driven call analytics. My background also includes recommender systems, real-time optimization, and cloud-native deployment. I'm currently pursuing an MS in Computer Science (ML specialization) from Georgia Tech with a 3.9 GPA.
Ethan Zhou
I am an interdisciplinary researcher with over 15 years of experience in biomedical informatics, AI, and health data science. My work spans machine learning, natural language processing, and multi-omics integration for clinical and translational research. I have led international teams, published extensively in peer-reviewed journals, and served as an associate editor in top scientific publications. I specialize in developing scalable, data-driven solutions for complex biomedical challenges.
Muhammad Midhat
I am a master's student in Computer Science at University Malaysia Pahang, specializing in AI/ML with a focus on computer vision and natural language processing. I have 5 years of experience developing innovative solutions in these areas. I am passionate about research, building real-world AI applications, and continuously learning new technologies. I thrive in collaborative environments that value creativity, growth, and impactful work.
Oscar Jordan Parra San Juan
I’m a data scientist and machine learning engineer with 5+ years of experience working on end-to-end ML solutions across industries such as Manufacturing, Energy, Software, among others. My background combines strong statistical analysis, machine learning, and software engineering skills.I’ve built models for predictive analytics, NLP, and computer vision, and have experience deploying them using tools like PyTorch, ONNX, and cloud platforms like GCP & AWS.
Techamana's talent pool features an extensive network of experienced Large Language Models developers ready to tackle your projects.
Begin HiringHow Techamana Vets Expert Large Language Models Talent
At Techamana, we maintain the highest standards in developer selection. Our Large Language Models experts undergo a comprehensive 4-step vetting process that evaluates technical skills, problem-solving abilities, communication skills, and team and culture fit. Only the top 5% of applicants pass our rigorous screening, ensuring you work with exceptional talent who can deliver outstanding results for your projects.
Technical Assessment
Rigorous coding challenges and problem-solving tests to evaluate Large Language Models proficiency and best practices.
Project Review
Thorough examination of past projects and contributions to open-source Large Language Models repositories to assess real- world experience.
Video Responses
Video responses for open-ended questions to assess problem-solving ability, communication skills, and team and culture fitment.
What to Look for When Hiring a Large Language Models Developer
When hiring an LLM engineer, prioritize transformer architecture mastery, prompt engineering, and fine-tuning with Hugging Face Transformers.
Candidates should integrate models into production, manage inference scaling, implement RAG, and follow ethical AI guidelines for high-impact NLP solutions.
Learn how Large Language Models is used in modern applications
Industry insights and best practices
Large Language Models (LLMs) are AI models trained on extensive datasets to understand, generate, and manipulate human language. Modern LLM applications include content generation, chatbots, coding assistance, summarization, and retrieval-augmented generation (RAG).
Content Generation
LLMs are used to create articles, marketing copy, reports, and creative writing at scale.
Chatbots and Virtual Assistants
LLMs power conversational agents that handle customer support, internal queries, and personal assistants.
Coding Assistance
LLMs like GitHub Copilot and Code Llama assist developers by suggesting, generating, and debugging code.
Summarization and Information Extraction
LLMs summarize long documents, extract key information, and aid in knowledge management workflows.
Retrieval-Augmented Generation (RAG)
LLMs are combined with search systems to provide more accurate, up-to-date, and context-specific answers.
Fine-tuning and Custom LLM Development
Organizations fine-tune base LLMs on domain-specific data to create tailored AI solutions.
The Techamana Advantage
Majority of our clients choose to continue working with our talent after their initial project
Our screening and matching process ensures exceptional talent are matched to your precise needs.
Start HiringFAQs
Hiring Large Language Models Developers is easy with Techamana
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Tell us your needs
Share your project requirements, timeline, and the specific Large Language Models skills you're looking for.
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