We are seeking a mid-level Machine Learning Engineer to join our Data Science, Reporting & Analytics team.

This role will focus on designing, developing, and deploying ML models that drive insights and automation across enterprise platforms.

The ideal candidate will have strong algorithmic thinking, hands-on experience with ML frameworks, and a collaborative mindset to work closely with data scientists and engineers.

Key Responsibilities :

- Model Development : Build, train, and validate machine learning models using Python, TensorFlow, PyTorch, or similar frameworks.

- Data Preparation : Collaborate with data engineers to source, clean, and transform data for modeling purposes.

- Deployment & Monitoring : Package models for deployment using MLOps tools; monitor performance and retrain as needed.

- Feature Engineering : Design and implement robust feature pipelines to improve model accuracy and efficiency.

- Collaboration : Work closely with analysts, product teams, and business stakeholders to translate requirements into ML solutions.

- Governance & Compliance : Ensure models adhere to data privacy, security, and ethical AI standards.

- Documentation & Support : Maintain model documentation and provide support for production ML workflows.

Skills & Qualifications :

- 812 years of experience in machine learning or applied data science roles.

- Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).

- Experience with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).

- Strong understanding of statistics, model evaluation, and optimization techniques.

- Familiarity with version control, CI/CD, and MLOps practices.

- Excellent problem-solving and communication skills.

Preferred Experience :

- Exposure to NLP, computer vision, or time-series modeling.

- Experience integrating ML models into enterprise applications or data platforms.

- Prior work in ed-tech or large-scale analytics environments is a plus.