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AI/ML Engineer (NLP & Generative AI)

ZAPNIX LLC·US·Remote Friendly

Posted 1w ago

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About the Role

Job Overview We are seeking a dynamic and innovative AI/ML Engineer specializing in Natural Language Processing (NLP) and advanced machine learning techniques to join our cutting-edge technology team. In this role, you will develop, optimize, and deploy sophisticated AI models that enhance our data-driven solutions, leveraging big data platforms and state-of-the-art frameworks. Your expertise will drive the transformation of complex data into actionable insights, empowering our organization to stay ahead in a rapidly evolving digital landscape. This position offers an exciting opportunity to work on impactful projects utilizing the latest in AI and machine learning technologies. Duties • Design, develop, and implement NLP models for language understanding, sentiment analysis, and conversational AI applications using frameworks such as TensorFlow and other machine learning tools. • Conduct model training and fine-tuning on large datasets utilizing unsupervised learning techniques to improve accuracy and efficiency. • Build scalable data pipelines with ETL processes to extract, transform, and load data from diverse sources into optimized databases for analysis. • Collaborate with cross-functional teams to integrate AI solutions into existing systems, ensuring seamless deployment and performance optimization. • Utilize cloud services like AWS for model deployment, management, and scaling of machine learning applications in production environments. • Perform data mining and analysis using SQL, Python, R, SAS, Spark, Hadoop, Talend, and Looker to uncover insights that inform strategic decisions. • Design robust database schemas and implement database design best practices to support large-scale data storage needs. • Develop algorithms for natural language processing tasks such as entity recognition, language modeling, and semantic understanding. • Apply machine learning frameworks like TensorFlow and Spark MLlib to accelerate model development cycles while maintaining high standards of quality. • Engage in continuous research on emerging AI trends including quantum engineering applications relevant to natural language processing and big data analytics. Skills • Proficiency in programming languages such as Python, Java, C, VBA, Bash (Unix shell), with a strong focus on Python for machine learning workflows. • Extensive experience with cloud platforms like AWS for deploying scalable AI/ML solutions. • Deep understanding of NLP techniques including language modeling, text classification, entity recognition, and semantic analysis. • Expertise in machine learning frameworks such as TensorFlow, Spark MLlib, Hadoop ecosystem tools for big data processing. • Knowledge of unsupervised learning methods including clustering algorithms and dimensionality reduction techniques. • Strong background in database design principles along with hands-on experience with SQL databases and linked data concepts. • Familiarity with ETL tools like Talend for efficient data integration workflows. • Experience with analytics tools such as Looker for visualization and reporting of insights derived from complex datasets. • Ability to develop models for deployment into production environments ensuring scalability and reliability. • Understanding of quantum engineering principles as they relate to advanced AI applications is a plus. Join us if you’re passionate about pushing the boundaries of artificial intelligence through innovative NLP solutions! We value energetic problem-solvers eager to make a tangible impact by transforming raw data into powerful insights that shape the future of technology. Job Type: Contract Work Location: Remote

What you'll do

  • In this role, you will develop, optimize, and deploy sophisticated AI models that enhance our data-driven solutions, leveraging big data platforms and state-of-the-art frameworks
  • Your expertise will drive the transformation of complex data into actionable insights, empowering our organization to stay ahead in a rapidly evolving digital landscape
  • This position offers an exciting opportunity to work on impactful projects utilizing the latest in AI and machine learning technologies
  • Design, develop, and implement NLP models for language understanding, sentiment analysis, and conversational AI applications using frameworks such as TensorFlow and other machine learning tools
  • Conduct model training and fine-tuning on large datasets utilizing unsupervised learning techniques to improve accuracy and efficiency
  • Build scalable data pipelines with ETL processes to extract, transform, and load data from diverse sources into optimized databases for analysis
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems, ensuring seamless deployment and performance optimization
  • Utilize cloud services like AWS for model deployment, management, and scaling of machine learning applications in production environments
  • Perform data mining and analysis using SQL, Python, R, SAS, Spark, Hadoop, Talend, and Looker to uncover insights that inform strategic decisions
  • Design robust database schemas and implement database design best practices to support large-scale data storage needs
  • Develop algorithms for natural language processing tasks such as entity recognition, language modeling, and semantic understanding
  • Apply machine learning frameworks like TensorFlow and Spark MLlib to accelerate model development cycles while maintaining high standards of quality
  • Engage in continuous research on emerging AI trends including quantum engineering applications relevant to natural language processing and big data analytics

Requirements

  • Proficiency in programming languages such as Python, Java, C, VBA, Bash (Unix shell), with a strong focus on Python for machine learning workflows
  • Extensive experience with cloud platforms like AWS for deploying scalable AI/ML solutions
  • Deep understanding of NLP techniques including language modeling, text classification, entity recognition, and semantic analysis
  • Expertise in machine learning frameworks such as TensorFlow, Spark MLlib, Hadoop ecosystem tools for big data processing
  • Knowledge of unsupervised learning methods including clustering algorithms and dimensionality reduction techniques
  • Strong background in database design principles along with hands-on experience with SQL databases and linked data concepts
  • Familiarity with ETL tools like Talend for efficient data integration workflows
  • Experience with analytics tools such as Looker for visualization and reporting of insights derived from complex datasets
  • Ability to develop models for deployment into production environments ensuring scalability and reliability
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