AI / Machine Learning Engineer

SUMMARY:

Brief Description:

POSITION INFO:

Job & Company Description:

Key Responsibilities:

• Design, develop, train, and deploy machine learning models and algorithms.
• Build scalable AI solutions using frameworks such as TensorFlow, PyTorch, or Keras.
• Develop and optimize predictive models using supervised, unsupervised, and reinforcement learning.
• Perform data preprocessing, feature engineering, and model validation.
• Build and maintain end-to-end ML pipelines (data ingestion, training, deployment).
• Apply advanced statistical and mathematical techniques to solve business problems.
• Work with NLP, Computer Vision, or Generative AI (depending on project requirements).
• Deploy models into production environments using MLOps tools (Docker, Kubernetes, MLflow, Airflow, etc.).
• Collaborate with cross-functional teams (Data Engineering, BI, Software Development).
• Document models, processes, and research findings.

Job Experience and Skills Required:

• Completed Degree in: Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics / Statistics, Or a related field

• AI / ML Certifications such as: Google Professional Machine Learning Engineer, AWS Machine Learning Specialty, Microsoft Azure AI Engineer Associate, TensorFlow Developer Certification or IBM AI Engineering

• Minimum 2 years real-world experience working as an AI / Machine Learning Engineer.
• Hands-on experience building, training, and deploying ML models.

• Strong experience with Python (NumPy, Pandas, Scikit-learn, etc.)
• Deep learning frameworks: TensorFlow, PyTorch, Keras
• Experience with NLP, Computer Vision, or Time-Series modelling
• Experience deploying ML models into production
• Understanding of MLOps principles
• Experience with REST APIs and integrating ML into applications
• Solid knowledge of SQL / NoSQL databases
• Cloud exposure: Azure, AWS, or GCP
• Strong mathematical, statistical, and analytical skills

• Experience with Generative AI / LLMs
• Experience with CI/CD pipelines
• Knowledge of Docker, Kubernetes, MLflow, Databricks
• Experience working with big data tools (Spark, Hadoop)

Apply now!