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AI Engineer

Responsibilities

Design, Develop and implement AI and advanced analytics solutions including Large Language Models (LLMs) for automation and chatbot applications
Conduct experiments with new algorithms and technologies, stay updated with the latest industry trends, and apply them to business problems.
Train and optimize AI/ML models to meet performance and accuracy benchmarks.
Deploy models into production environments, monitor performance, and improve based on real-time data.
Collaborate with cross-functional teams, including business team, developers, and other stakeholders to ensure AI-driven solutions meet business goals.
Maintain clear documentation of models, workflows, and results.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
Proven experience in AI/ML model development (e.g., deep learning, NLP, reinforcement learning, computer vision).
Strong programming skills in Python, TensorFlow, PyTorch, and other AI/ML frameworks.
Experience with cloud platforms (AWS, Google Cloud, Azure) and deploying AI solutions in a cloud environment.
Solid understanding of data structures, algorithms, and software engineering best practices.
Proficiency in data processing tools (e.g., SQL, NoSQL, Hadoop, Spark).
Experience with MLOps and model lifecycle management tools.
Excellent problem-solving skills and ability to work independently as well as in a team.
Knowledge of various machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.) with practical experience.
Experience in using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large datasets.
Strong passion to identify and solve business problems using data science techniques.
Demonstrate troubleshooting and analytical skills to address complex data challenges.
Possess good communication, storytelling, presentation, and collaboration skills to convey findings effectively.
Mindset aligned with Agile methodology principles to adapt to dynamic project requirements.
A good team player with a collaborative mindset.

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