AI/ML

AI/ML Job description:
As an AI/ML Engineer/Data Scientist, you will play a pivotal role in developing and implementing
cutting-edge AI and machine learning solutions to solve complex business problems. You will
collaborate with cross-functional teams to design, develop, and deploy AI/ML models and
algorithms, contributing to the advancement of our products and services.
Responsibilities:
Data Collection and Preprocessing:
● Gather, clean, and preprocess large datasets for analysis and modeling.
● Implement data pipelines and ETL processes to ensure data quality and
accessibility.
Model Development:
● Design, develop, and optimize machine learning models and algorithms.
● Experiment with different approaches and techniques to improve model
performance.
● Perform feature engineering and selection to enhance model accuracy.
Model Training and Evaluation:
● Train machine learning models using appropriate tools and frameworks.
● Evaluate model performance using relevant metrics and implement
improvements as necessary.
Deployment and Integration:
● Deploy machine learning models into production environments.
● Collaborate with software engineers to integrate models into existing systems.
Monitoring and Maintenance:
● Implement monitoring solutions to track model performance in real-time.
● Perform regular model maintenance and updates as needed.
Collaboration and Communication:
● Work closely with cross-functional teams, including data engineers, software
developers, and domain experts.
● Communicate complex technical concepts and results to non-technical
stakeholders.
Research and Innovation:
● Stay up-to-date with the latest advancements in AI/ML and data science.
● Propose and explore innovative solutions to solve business challenges.
Requirements :
● Bachelor’s degree in Computer Science, Data Science, or a related field (Master’s or
Ph.D. preferred).
● Proven experience in developing and deploying machine learning models in real-world
applications.
● Proficiency in programming languages such as Python and libraries like TensorFlow,
PyTorch, or scikit-learn.
● Strong knowledge of data preprocessing, feature engineering, and model evaluation.
● Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization
(e.g., Docker).
● Familiarity with data visualization tools and techniques.
● Excellent problem-solving skills and the ability to work independently and in teams.
● Strong communication and presentation skills.
● Knowledge of software development and version control (e.g., Git) is a plus.