AI Engineer
Role details
Job location
Tech stack
Job description
Join our innovative team as an AI Engineer and be at the forefront of developing cutting-edge artificial intelligence solutions that transform data into actionable insights. In this role, you will design, build, and deploy advanced AI models and machine learning frameworks to solve complex business challenges. Your expertise will drive the implementation of scalable AI systems, leveraging big data technologies and cloud services to deliver impactful results. We are seeking passionate professionals eager to push the boundaries of AI and contribute to pioneering research and development initiatives., * Develop, train, and evaluate machine learning models utilizing frameworks such as TensorFlow, ensuring high accuracy and efficiency for diverse applications.
- Design and implement scalable big data systems using tools like Hadoop, Spark, and ETL processes to manage large datasets effectively.
- Apply statistical modeling and analysis techniques using tools such as R, SAS, and statistical analysis software to extract meaningful insights from complex data.
- Integrate AI models into production environments through model deployment strategies, ensuring robustness and scalability across cloud platforms like AWS.
- Collaborate with cross-functional teams to develop natural language processing (NLP) applications and generative AI solutions that enhance user engagement.
- Conduct model training sessions focusing on predictive modeling analysis, model evaluation, and continuous improvement cycles.
- Utilize SQL databases, data mining techniques, and database design principles to optimize data storage and retrieval for analytics purposes.
Requirements
- Proven experience in machine learning/AI-based analysis with a strong understanding of AI implementation in real-world scenarios.
- Hands-on expertise with machine learning frameworks such as TensorFlow, Spark MLlib, or similar tools.
- Familiarity with big data systems including Hadoop ecosystem components (HDFS, MapReduce) and Spark implementation for large-scale data processing.
- Proficiency in programming languages including Python, Java, C, VBA, Bash (Unix shell), with additional knowledge of SQL for database management.
- Experience with cloud-based machine learning services on platforms like AWS or similar providers is highly desirable.
- Knowledge of natural language processing (NLP), predictive modeling analysis, statistical analysis tools, and model evaluation techniques.
- Understanding of data analytics workflows involving data mining, data integration (Talend), Looker for visualization, and data scalability considerations.