Devsinc is looking for passionate Associate Software Engineers - AIML to join its team.
Requirements:
- Work on data preprocessing, cleaning, and transforming raw data into a usable format for modeling.
- Collaborate with senior engineers to optimize machine learning models for performance and scalability.
- Participate in the training and fine-tuning of models to improve accuracy and efficiency.
- Conduct research on emerging AI/ML techniques and contribute to proof-of-concept development.
- Document model development, research, and performance metrics for future reference and learning.
- Collaborate with cross-functional teams to understand business problems and provide AI/ML-driven solutions.
- Assist in developing deployment pipelines for ML models, ensuring they are scalable and efficient.
- Assist in the development and implementation of machine learning models for various business applications.
- Strong understanding of machine learning algorithms such as regression, classification, clustering, and deep learning techniques.
- Familiarity with Python and libraries like TensorFlow, Keras, PyTorch, or scikit-learn.
- Basic knowledge of data preprocessing, data manipulation, and feature engineering.
- Understanding of statistics and its application in machine learning (probability distributions, hypothesis testing, etc.).
- Familiarity with linear algebra and calculus for understanding ML models.
- Knowledge of SQL for data querying and experience with handling large datasets.
- Familiarity with version control using Git.
- Strong problem-solving skills and a keen interest in developing AI-driven solutions.
- Ability to work effectively in a team environment and collaborate with cross-functional teams.
- Willingness to continuously learn and stay updated with the latest trends and advancements in AI/ML technologies.
Qualification: - Bachelor’s degree in Computer Science, Engineering, Data Science, or any related field.
- A strong foundation in mathematics, statistics, and computer science.
- Understanding of machine learning concepts and algorithms is preferred but not required.
- Exposure to AI/ML through academic projects, internships, or online courses is a plus.
