POSITION SUMMARY

We are seeking a highly motivated Junior AI/ML Engineer to join our growing team. In this role, you will contribute to the design, development, and deployment of machine learning models and AI solutions that support our clients’ digital transformation and automation initiatives. This is an excellent opportunity for early-career professionals eager to learn, grow, and make an impact in a collaborative, mission-driven environment.

REQUIRED QUALIFICATIONS

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field. Or 2 years work experience in software engineering with some AI/ML practices.
• Proficiency in Python and familiarity with ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
• Strong understanding of linear algebra, probability, statistics, and optimization techniques.
• Experience with data manipulation tools (e.g., pandas, NumPy) and data visualization libraries (e.g., Matplotlib, Seaborn).
• Knowledge of version control systems (e.g., Git) for collaborative development.
• Analytical mindset and a passion for solving complex problems.
• Excellent communication and teamwork skills.

PREFERRED QUALIFICATIONS

• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Familiarity with Agile methodologies and DevOps practices.
• Exposure to natural language processing (NLP), computer vision, or cybersecurity applications is a plus.
• Internship or project experience in AI/ML, including participation in Kaggle competitions or open-source contributions.

• Assist in collecting, cleaning, and preprocessing structured and unstructured data for use in machine learning models.
• Support the design, training, testing, and deployment of machine learning and deep learning models for real-world applications.
• Collaborate with senior engineers and cross-functional teams to identify, extract, and engineer relevant features for model performance.
• Analyze and evaluate model performance using appropriate metrics; help optimize models for accuracy and efficiency.
• Contribute to the integration and deployment of ML models into production environments using APIs or deployment pipelines.
• Stay current with the latest AI/ML trends, tools, and best practices; experiment with innovative techniques under guidance.
• Document datasets, models, experiments, and code to ensure reproducibility and knowledge sharing.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.