- Assist in developing, training, and optimizing machine learning models for various applications.

- Work with large datasets, performing data preprocessing, feature engineering, and model evaluation.

- Collaborate with data scientists and software engineers to integrate ML models into production environments.

- Conduct experiments to improve model accuracy and efficiency.

- Write clean, efficient, and well-documented code for ML model development.

- Stay updated with the latest advancements in ML algorithms and technologies.

Key Competencies :

- Strong analytical and problem-solving skills.

- Ability to understand and implement ML algorithms effectively.

- Good communication skills to collaborate with cross-functional teams.

- Attention to detail and a structured approach to work.

- GenAI : Curiosity and experimentation with LLMs & GenAI tools (e., ChatGPT, Gemini) and prompt tuning.

- MLOps : Learning foundations of model deployment, version control, and experiment tracking.

Relevant Work Exp : 2-5 years.

Technical Skills :

- Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn.

- Experience with data manipulation using Pandas and NumPy.

- Familiarity with cloud platforms like AWS, Azure, or GCP for ML model deployment.

- Knowledge of SQL and database management.

- Understanding of software development best practices (Git, Docker, CI/CD).

Behavioral Competencies :

- Adaptability : Open to learning and applying new ML techniques, tools, and frameworks.

- Learning Agility : Willingness to experiment, analyze failures, and continuously improve skills.

- Teamwork : Works collaboratively with peers, takes feedback constructively, and contributes to team success.

Certifications (Optional) :

- TensorFlow Developer Certification.

- AWS Certified Machine Learning Specialty.

- Microsoft Certified : Azure AI Engineer Associate.

- Google Professional Machine Learning Engineer.