Required Skills & Qualifications:

Programming Languages

• Python, Java/Scala: Commonly used in big data frameworks like Apache Spark.

• C++: Helpful for high-performance applications, such as those needing faster execution times.

Libraries and Frameworks

• TensorFlow, PyTorch, Keras & Scikit-learn

Data Manipulation and Analysis

• Pandas, NumPy, SQL & Data Wrangling

Machine Learning Concepts

• Supervised Learning: Understanding classification and regression models.

• Unsupervised Learning: Techniques such as clustering and dimensionality reduction.

• Reinforcement Learning: Familiarity with algorithms relevant to decision-making processes.

Tools and Platforms

• Jupyter Notebook: An interactive environment for exploratory data analysis and development.

• Git: Version control for managing codebases.

• Docker: For containerization of applications, ensuring consistency across environments.

• Cloud Platforms: Familiarity with AWS, Google Cloud,



or Azure for deploying ML models.

Software Development Skills

• APIs: Creating and consuming RESTful APIs for model deployment.

• Software Development Lifecycle (SDLC): Understanding the phases of software development and methodologies (e.g., Agile, DevOps).

• Testing and Debugging: Techniques for ensuring code quality and model performance.

Big Data Technologies

• Hadoop: For distributed data processing.

• Spark: For big data analytics and processing.

• NoSQL Databases: Such as MongoDB or Cassandra for handling unstructured data.

Must Have:

• Proficiency in Python

• Libraries and Frameworks - TensorFlow, PyTorch, Keras & Scikit-learn

• Exp in Git, Jupitor Notebook

• Data Maniplation Skills - Pandas, NumPy, SQL & Data Wrangling

• Machine Learning Concepts

📌 Ai Ml Engineer (OCR) (Bengaluru)
🏢 ALTEN
📍 Bengaluru