Python Developer Lead

About the Role:
We are seeking a skilled Python AI/ML Developer with 24 years of professional experience to join our dynamic team. The ideal candidate will be passionate about artificial intelligence and machine learning, proficient in Python, and capable of developing scalable AI solutions. You will work on cutting-edge projects, leveraging data-driven insights to solve real-world challenges.

Key Responsibilities:

AI/ML Development:

Design, develop, and deploy machine learning models and algorithms to solve business problems.
Optimize AI models for performance and scalability.
Data Preparation:

Clean, preprocess, and analyze large datasets to extract meaningful insights.
Work with structured and unstructured data from diverse sources.
Model Deployment:

Implement and maintain ML models in production environments.
Utilize frameworks such as TensorFlow, PyTorch, or Scikit-learn for development and deployment.
Collaboration:

Collaborate with cross-functional teams, including data engineers, analysts, and product managers, to align AI solutions with business objectives.
Present technical findings and results to stakeholders.
Research and Innovation:

Stay updated with the latest trends in AI/ML technologies and integrate best practices into projects.
Explore new tools and frameworks to enhance efficiency and accuracy.
Required Skills and Qualifications:

Education: Bachelors or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
Technical Proficiency:
Strong programming skills in Python.
Proficient in libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
Experience with data visualization tools (e.g., Matplotlib, Seaborn).
Knowledge of databases and SQL.
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) is a plus.
Experience:
2–4 years of experience in AI/ML development.
Hands-on experience with ML lifecycle, including data preparation, modeling, evaluation, and deployment.
Problem-Solving Skills: Strong analytical and critical-thinking abilities to solve complex problems.
Communication: Excellent written and verbal communication skills to collaborate with technical and non-technical stakeholders.
Preferred Qualifications:

Knowledge of deep learning techniques and NLP.
Experience with DevOps for ML pipelines (e.g., MLOps).
Understanding of reinforcement learning and advanced AI concepts.