ARTIFICIAL INTELLIGENCE / MACHINE LEARNING ENGINEER
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Mandatory Skills:
Proficiency in Python, TensorFlow, PyTorch, Scikit-learn
Experience with cloud platforms like AWS, Google Cloud Platform, or Azure
5-8 years of experience in AI/ML development
Key Responsibilities:
Design, develop, and deploy machine learning models and algorithms to solve complex business challenges.
Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to implement AI/ML solutions in real-world applications.
Analyze large datasets to extract meaningful insights and identify opportunities for optimizing processes and systems.
Develop and maintain AI/ML pipelines, ensuring scalability, reliability, and efficiency.
Work closely with the engineering team to integrate models into production systems.
Stay updated on the latest AI/ML trends, tools, and techniques to continually enhance the company s technology stack.
Optimize model performance and accuracy through testing, validation, and model tuning.
Contribute to code reviews, technical documentation, and overall system architecture design.
Required Qualifications:
5-8 years of professional experience in AI/ML engineering or related roles.
Strong proficiency in programming languages such as Python, R, or Java.
Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
Experience with data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with cloud platforms like AWS, Google Cloud, or Azure for AI/ML deployment.
Solid understanding of statistical analysis, probability, and data modeling.
Experience working with large-scale data processing tools like Hadoop, Spark, or similar frameworks.
Strong problem-solving skills and a data-driven approach to decision-making.
Preferred Qualifications:
Experience with natural language processing (NLP) or computer vision.
Familiarity with containerization technologies (Docker, Kubernetes) for AI/ML model deployment.
Prior experience working in an agile development environment.
Experience in working with MLOps pipelines and tools.