Ksolves - Artificial Intelligence/Machine Learning Engineer - Data Modeling (1-7 yrs)

Responsibilities :

- Execute POCs : Develop proof of concepts (POCs) and basic model implementation with minimal guidance.

- Develop ML Models : Train and optimise basic machine learning models, perform data preprocessing, and carry out exploratory data analysis.

- Work with Cloud APIs : Use ML/AI APIs from GCP (preferred), AWS, or Azure for simple model development and integration tasks.

- Handle Datasets : Work with small to medium-sized datasets for analysis and model training, ensuring data accuracy and usability.

- Collaborate with Teams : Work closely with senior engineers and cross-functional teams to integrate ML models into applications.

- Learn Advanced Techniques : Be proactive in learning and applying advanced concepts in machine intelligence, including areas like anomaly detection, fraud detection, or AI IoT.

Requirements :

- Education : Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

- Experience : 1+ year of experience in machine learning or data science, with a basic understanding of industry workflows.

- Programming Skills : Proficiency in Python with working knowledge of data manipulation and visualisation libraries like Scikit-learn and Pandas.

- Machine Learning Knowledge : Basic understanding of machine learning, statistical modelling, and AI domains such as NLP or computer vision, with the ability to build and deploy simple models.

- Cloud Platforms : Experience with cloud platforms (GCP preferred, AWS, Azure) and the ability to use their basic ML/AI services.

- ML DevOps and Virtualisation : Basic knowledge of versioning, model serving, and containerisation tools like Docker.

- Problem-Solving : Strong analytical and problem-solving skills, with a willingness to take on challenges in a dynamic environment.

- Communication Skills : Ability to clearly communicate technical findings to peers and stakeholders.