Posted:1 day ago|
Platform:
On-site
Contractual
· Design and implement machine learning models for classification, regression, recommendation, NLP, or computer vision tasks.
· Build and deploy ML pipelines using tools like TensorFlow, PyTorch, Scikit-learn, or MLflow.
· Collaborate with data scientists, data engineers, and product teams to integrate models into production systems.
· Analyze large, complex datasets to derive actionable insights and drive model development.
· Conduct experiments, tune hyperparameters, and evaluate model performance using industry-standard metrics.
· Ensure robustness, fairness, and scalability of machine learning systems.
· Monitor and maintain deployed models, including retraining and updating as needed.
· Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
· 3+ years of experience in machine learning, data science, or applied AI roles.
· Proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.).
· Experience with data manipulation tools (Pandas, NumPy) and SQL.
· Hands-on experience in deploying ML models into production (using REST APIs, Docker, Kubernetes, etc.).
· Solid understanding of ML algorithms, model evaluation, and overfitting/underfitting concepts.
· Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.
· Experience with NLP (e.g., BERT, GPT), computer vision (e.g., CNNs, OpenCV), or time-series forecasting.
· Exposure to MLOps tools and practices (e.g., MLflow, DVC, Kubeflow).
· Understanding of data engineering practices and pipeline automation.
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