AI ML Engineer

• Bachelor or equivalent degree from a reputed educational institute, preferably in computer programming, computer science, or a related field.
• Certification(s): Not mandatory, but certification in a relevant field is a plus.

• Utilize Python and its machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) to design, develop, and deploy machine learning models tailored to specific business needs.
• Continuously improve and optimize machine learning algorithms to enhance the accuracy and performance of predictive models.
• Employ data manipulation and analysis tools such as Pandas and NumPy to clean, transform, and analyze large datasets.
• Ensure data integrity and quality throughout the entire data pipeline, from collection to processing and analysis.
• Apply a strong understanding of machine learning algorithms, statistical methods, and data preprocessing techniques to analyze complex data sets.
• Perform exploratory data analysis to identify trends, patterns, and insights that can drive decision-making and strategy.
• Work with cloud platforms (e.g., AWS, GCP, Azure) to deploy machine learning models and manage computational resources efficiently.
• Utilize containerization technologies such as Docker to create scalable and reproducible environments for model development and deployment.

• Model Development: Design, develop, and optimize machine learning models and algorithms tailored to business needs, utilizing Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Data Analysis: Analyze complex datasets to extract meaningful insights and identify patterns that drive decision-making.
• Algorithm Implementation: Implement and validate machine learning algorithms and statistical methods, ensuring robustness and scalability.
• Code Optimization: Write clean, efficient, and maintainable code while adhering to best practices in software engineering.
• Collaboration: Work closely with cross-functional teams including data scientists, engineers, and product managers to integrate machine learning solutions into products and systems.
• Research and Innovation: Stay updated with the latest advancements in AI/ML technologies and techniques, and contribute to research and innovation within the team.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a collaborative and knowledge-sharing environment.
• Deployment: Manage the deployment and monitoring of machine learning models in production environments, ensuring high performance and reliability.

• EOBI
• Provident Fund
• Medical Health Insurance
• Annual Leaves
• Casual leaves
• Sick Leaves
• Bereavement Leaves
• Marriage Leaves
• Paternity Leaves
• Maternity Leaves
• Recreational area for in-house games

• A growth mindset through the help of experienced and helpful Mentors. Ikonic is made up of passionate individuals who aim to support each other in their training as well as day-to-day tasks.
• A Dynamic Environment where we focus on encouraging initiatives, promoting agility and creating a work/life balance. We know the value you bring in and we aim to nurture it.
• Market Competitive Compensation based upon your professional qualifications and skill set.
• As an Equal employment opportunity provider. All employment associated decisions are based on an individual's merit.

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