AI/ML Engineer

About the Role

We are seeking a Senior AI/ML Engineer to join our clients AI team and contribute to the development of cutting-edge intelligent systems. In this role, youll be responsible for designing, training, and deploying machine learning models that power innovative features across devices and services. This is an exciting opportunity to work with a global technology leader in the telecommunications sector, applying your expertise to real-world applications that impact millions of users.

Contract: 12 months (with potential 12-month extension based on performance)

Client: A leading multinational telecommunications company (name disclosed at interview)

Responsibilities

• Develop and fine-tune machine learning algorithms.
• Conduct experiments, evaluate model performance, and suggest improvements.
• Lead and collaborate with engineers to implement production-ready AI solutions.
• Document processes and results for scalability

Requirements

• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field.
• 5-7 years of experience in developing and deploying machine learning models.
• At least 3 years of experience leading a team.
• Proficiency in Python and popular ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Strong understanding of data preprocessing, model evaluation, and hyperparameter tuning.
• Experience with SQL, Pandas, NumPy, and working with structured and unstructured data.
• Familiarity with MLOps tools (Docker, Kubernetes, MLflow, Airflow) is a plus.
• Experience with cloud platforms (AWS, Azure, or GCP) preferred.

Programming & ML Frameworks

• Python
• TensorFlow
• PyTorch
• scikit-learn
• XGBoost / LightGBM (common in practical ML pipelines)
• Data & Analytics
• NumPy, Pandas
• SQL
• Jupyter Notebooks
• Data preprocessing & feature engineering tools
• Cloud / Infrastructure
• AWS (S3, SageMaker, Lambda, ECS)
• Azure (ML Studio, Blob Storage)
• GCP (AI Platform, BigQuery)
• (Any of the threewhichever the client prefers)
• Version Control & CI/CD
• Git / GitHub / GitLab
• Jenkins, GitHub Actions, or GitLab CI

• Development & Experimentation Tools
• TensorBoard
• Weights & Biases (W&B) or Neptune.ai
• ONNX (optional but common for deployment/optimization)
• Other Useful Skills (common for telecom/edge AI)
• Experience with edge AI model optimization (TensorRT, CoreML, TFLite)