Senior AI/ML Developer

Job Title: Senior AI/ML Developer

Experience: 8-10 Years

Location: [Mumbai]

Job Type: [Full-Time]

Key Responsibilities:

 Lead the design and development of machine learning models using Python, TensorFlow, and other AI/ML frameworks.

 Build, train, and optimize machine learning models to improve business processes and outcomes.

 Work with large datasets in distributed environments using PySpark, Hadoop, and HIVE.

 Analyze and preprocess data, clean datasets, and implement feature engineering techniques.

 Collaborate with data scientists, engineers, and product teams to deliver AI-powered solutions.

 Conduct model analysis and performance evaluations, ensuring the accuracy and effectiveness of ML models.

 Maintain and document machine learning workflows and processes in a collaborative environment.

 Utilize Git for version control and JIRA for task management and project tracking.

 Continuously monitor and improve model performance, ensuring scalability and efficiency.

 Stay updated with the latest trends and advancements in AI/ML to enhance development capabilities.

Skills and Qualifications:

 8-10 years of experience in AI/ML development with a strong focus on model building and analysis.

 Strong proficiency in Python for developing machine learning algorithms and solutions.

 Experience with PySpark, Hadoop, and HIVE for working with large datasets in a distributed environment.

 Hands-on experience with TensorFlow for deep learning model development and training.

 Solid understanding of machine learning algorithms, techniques, and frameworks.

 Experience with notebooks (e.g., Jupyter) for model development, analysis, and experimentation.

 Strong skills in model evaluation, performance tuning, and optimization.

 Proficiency with Git for version control and JIRA for project management.

 Excellent problem-solving skills and attention to detail.

 Strong communication skills and ability to collaborate with cross-functional teams.

Preferred Qualifications:

 Experience with cloud platforms (AWS, Azure, GCP) for machine learning deployment.

 Knowledge of additional AI/ML frameworks such as Keras, Scikit-learn, or PyTorch.

 Familiarity with CI/CD pipelines and DevOps practices for machine learning.

 Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn).

 Background in statistical analysis and data mining.