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

5-8 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.

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Sr Machine Learning Engineer