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AI / ML Engineer

AI / ML Engineer

DraconXThane, IN
5 days ago
Job description

Company Description

DraconX transforms innovative ideas into intelligent, scalable digital solutions. As a leader in AI business automation and AI-driven SaaS platforms, the company specializes in building MVPs, custom software, and automation systems to drive growth for startups and enterprises. Leveraging expertise in AI, data analytics, and cloud technologies, DraconX creates solutions that streamline operations, provide real-time insights, and enable smarter and faster business processes. With a collaborative approach, the DraconX team works closely with clients from initial concept to deployment, delivering strategic and tailored products to meet real business needs in a competitive digital landscape.

Role Description

This is a full-time remote role for an AI / ML Engineer. The AI / ML Engineer will be responsible for designing, building, and optimizing machine learning models and algorithms to solve complex business challenges. Key tasks include developing and implementing neural network architectures, performing statistical analysis, and creating innovative solutions for pattern recognition problems. Additionally, this role involves close collaboration with cross-functional teams to integrate AI models into scalable software systems.

Qualifications

  • Proficiency in developing and optimizing Machine Learning models, with expertise in Neural Networks and Pattern Recognition
  • A strong foundation in Computer Science principles, including Algorithms and data structures
  • Knowledge of advanced Statistics, including probability, statistical modeling, and data analysis techniques
  • Experience with programming languages such as Python, R, or Java, and familiarity with frameworks like TensorFlow or PyTorch
  • A strong problem-solving mindset and ability to work independently in a remote setting
  • Master's or Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field; relevant certifications are a plus
  • Experience in cloud-based machine learning deployments and knowledge of AWS, Azure, or Google Cloud is advantageous
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