Company Overview

At Huemn, we understand the challenges of running a busy photography studio. That's why we've developed a cutting-edge studio management tech tool that streamlines the entire process, from managing projects and teams to collecting payments and leads. Our cloud galleries with AI face recognition make it easy to organize and share photos with clients, while our project management tools ensure that every project is completed on time and to the highest standards.

Job Overview

We are looking for a passionate and skilled Junior Python ML Developer to join our team in Hyderabad. The ideal candidate should have 1 to 3 years of work experience with a focus on machine learning and deep learning. This is a full-time position that requires a strong foundation in Python programming and experience in data preprocessing, statistical analysis, and model evaluation.

Qualifications and Skills

• Proficiency in Python programming, with a solid understanding of libraries like NumPy and Pandas.
• Experience with data preprocessing techniques such as data cleaning, normalization, and transformation.
• Knowledge of machine learning algorithms (Mandatory skill) and their applications.
• Hands-on experience with deep learning frameworks like TensorFlow or PyTorch (Mandatory skill).
• Expertise in data visualization tools like Matplotlib and Seaborn (Mandatory skill).
• Familiarity with statistical analysis, including hypothesis testing and inferential statistics.
• Experience with natural language processing techniques and libraries such as NLTK or SpaCy.
• Skills in model evaluation, including accuracy metrics, confusion matrix, and cross-validation techniques.

Roles and Responsibilities

• Develop and implement machine learning models to enhance the capabilities of our studio management tech tool.
• Collaborate with cross-functional teams to integrate machine learning algorithms into various features of the platform.
• Perform data preprocessing, including data cleaning and transformation, to ensure high-quality datasets are used in model training.
• Conduct statistical analyses to derive insights and guide model development.
• Utilize deep learning frameworks for tasks such as image recognition and natural language processing.
• Create data visualizations to communicate findings and model performance to stakeholders.
• Evaluate and optimize models using various performance metrics and validation techniques.
• Keep up-to-date with the latest advancements in machine learning and implement best practices in model development.