Senior AIML Engineer

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

Client: A leading multinational telecommunications company Motorola

We are seeking a Senior AI/ML Engineer to join our clients AI team and contribute to the development of cutting-edge intelligent 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.

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.

Tech Stack

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

ONNX (optional but common for deployment/optimization)

Other Useful Skills (common for telecom/edge AI)

Experience with edge AI model optimization (TensorRT CoreML TFLite)