Artificial Intelligence Engineer

About the Role:

We are seeking a highly motivated and enthusiastic AI Engineer to join our growing Artificial Intelligence team at DataFlow Group. This entry-level role is perfect for a recent graduate or early-career professional who is passionate about machine learning, deep learning, and building innovative AI-driven solutions. The successful candidate will work closely with senior engineers and data scientists to implement, test, and maintain machine learning models and pipelines.

Duties and Responsibilities:

Assist in the collection, cleaning, and preprocessing of large datasets for ML model training.

Implement, test, and tune various machine learning algorithms, including Regression, Classification, and Clustering techniques, and prototypes under guidance.

Work on specific domain models such as Computer Vision, Image Processing, and Natural Language Processing (NLP).

Write and maintain clean, efficient, and well-documented code primarily in Python.

Participate in the deployment and monitoring of ML models in production environments.

Conduct basic statistical analysis, A/B testing, and comprehensive model evaluation.

Stay up-to-date with the latest AI/ML research and technologies.

Collaborate with cross-functional teams (e.g., software engineering, data science) to integrate AI/ML solutions.

Qualifications:

Bachelor's degree in Computer Science, Engineering, AI, or a related field.

Familiarity with data structures, algorithms, and software design principles.

Proficiency in Python and experience with core ML libraries (e.g., Scikit-learn, Pandas, NumPy).

Familiarity with at least one deep learning framework (e.g., TensorFlow or PyTorch etc).

Solid understanding of basic machine learning concepts (e.g., supervised vs. unsupervised learning, model evaluation metrics, cross-validation, and hyperparameter tuning).

Basic knowledge of SQL and database concepts.

Excellent problem-solving skills and a willingness to learn rapidly.

Prior internship or project experience in AI/ML, demonstrating practical feature

engineering or model development skills.

Experience with version control systems (e.g., Git).

Exposure to cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker) for potential ML deployment.

Demonstrated ability to read, understand, and summarize complex research papers. Evidence of academic publications.

Optimization Expert: Proven experience in optimizing application load times, rendering performance, and resource management.

Grit & Speed: You thrive in high-pressure environments and enjoy the challenge of meeting tight deadlines without compromising on quality.