Hire Expert Natural Language Processing Developers
Techamana connects you with the World's Best 5% of Natural Language Processing talent. Work with elite Natural Language Processing developers who have passed our rigorous vetting process, ensuring you get the best expertise for your groundbreaking projects.
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Featured Natural Language Processing 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.
Tianchang Liu
Senior Machine Learning Engineer with 10+ years of experience building and deploying scalable AI systems across computer vision, NLP, generative AI, and MLOps. I've led end-to-end ML projects from real-time edge inference to LLM-powered applications, with a focus on performance, reliability, and impact. My work spans startups and enterprises, including Mashgin, Gensyn, Voyage, and Amazon. Skilled in Python, Go, Kubernetes, TensorRT, DeepSpeed, and cloud infrastructure, I specialize in shipping production-grade AI that solves real-world problems.
Ramesh
Senior Data and AI Engineer with 16+ years of experience across data engineering, analytics, and AI/ML. Proven track record in building cloud-native data platforms, implementing GenAI solutions, LLMs, and enterprise-scale RAG pipelines. Expert in Snowflake, AWS, and BI tools like Looker and Tableau. Adept at MLOps, DBT, and AI DevOps for deploying scalable, secure, and intelligent systems. Strong leadership in AI projects, enabling business transformation through automation, data-driven decision-making, and next-gen GenAI applications.
Emrah
Highly accomplished Senior AI/ML Data Scientist with over a decade of expertise in developing, optimizing, and deploying sophisticated machine learning models, deep learning frameworks, and AI-driven solutions. Proficient in designing and implementing advanced predictive analytics, large-scale natural language processing (NLP) architectures, and state-of-the-art computer vision applications. Extensive experience in Python programming, leveraging frameworks such as TensorFlow, PyTorch, Scikit-learn, FastAPI, and Flask for end-to-end AI model development and deployment. Demonstrated expertise in MLOps, CI/CD pipelines, containerization, and cloud-based deployments using AWS, Azure, GCP, Docker, Kubernetes, MLflow, Terraform, and Snowflake.
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.
Selvakumar Ulaganathan
I’m an AI/ML Consultant with 10+ years of experience delivering end-to-end machine learning solutions across sectors like pharma, energy, insurance, and manufacturing. I specialize in building scalable AI systems including GenAI, computer vision, and edge AI using tools like PyTorch, TensorFlow, Azure, and AWS. As Founder of MLGlow, I’ve led diverse AI projects from R&D to production, helping clients solve real-world problems with cutting-edge technologies. I thrive in fast-paced, collaborative environments focused on innovation and impact.
Muhhammad Adnan
I am an experienced QA Analyst with a strong background in collaborating with Product Owners and Developers to analyze business specifications and ensure high-quality software delivery. My expertise lies in managing multiple applications simultaneously, prioritizing tasks effectively to meet project deadlines. Key Responsibilities: Test Planning and Execution: Developed and executed comprehensive test plans and test cases, leveraging QTP for data-driven testing. Functional Testing: Created mock accounts for functional tests, ensuring thorough testing of application features. Local Testing: Conducted local testing to validate features before they proceed to the staging environment, ensuring a seamless transition. API Testing: Maintained and tested API calls using ReadyAPI.
Henry Blauth
I'm a senior data engineer with a strong track record of designing and optimizing data infrastructure to unlock business value. With deep expertise in Python, SQL, Airflow, and AWS, I’ve led impactful projects—from building ML-powered job classification systems to boosting CRM engagement by 197% and cutting pipeline runtimes by 800%. I thrive in cross-functional environments, bringing analytical rigor, clean engineering practices, and a focus on outcomes. My experience spans startups to established platforms, and I’m passionate about solving complex data challenges that drive real results.
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.
Heba Abdelhadi
Data Analyst/Data Scientist with hands-on experience in data preprocessing, visualization, and machine learning. Skilled in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, Keras, Matplotlib, and Seaborn. Experienced in regression, classification, clustering, recommendation systems, and deep learning. Applied data science across domains including healthcare, fraud detection, and mobile apps. Strong analytical skills, scientific approach, and a background in chemical engineering.
Techamana's talent pool features an extensive network of experienced Natural Language Processing developers ready to tackle your projects.
Begin HiringHow Techamana Vets Expert Natural Language Processing Talent
At Techamana, we maintain the highest standards in developer selection. Our Natural Language Processing 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 Natural Language Processing proficiency and best practices.
Project Review
Thorough examination of past projects and contributions to open-source Natural Language Processing 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 Natural Language Processing Developer
When hiring an NLP engineer, prioritize tokenization, embeddings (Word2Vec, BERT), and transformer-based modeling.
Candidates should process text with SpaCy/NLTK, implement sequence tasks, fine-tune pretrained models, and deploy pipelines in containerized environments.
Learn how Natural Language Processing is used in modern applications
Industry insights and best practices
Natural Language Processing (NLP) involves enabling computers to understand, interpret, and generate human language. Modern NLP utilizes deep learning techniques for advanced tasks.
Machine Translation
NLP is used to build machine translation systems, which translate text from one language to another.
Sentiment Analysis
NLP is used to analyze the sentiment expressed in text, determining whether the text is positive, negative, or neutral.
Text Summarization
NLP is used to summarize large amounts of text into shorter, more concise summaries.
Chatbots
NLP is used to build chatbots, which can interact with users in natural language.
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 Natural Language Processing Developers is easy with Techamana
Connect with top-tier Natural Language Processing developers in just a few simple steps. Our streamlined process ensures you find the perfect match for your project needs.
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Share your project requirements, timeline, and the specific Natural Language Processing skills you're looking for.
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