AI/ML Engineer

✔️ Expertise in designing, developing, and deploying machine learning and deep learning models for real-world applications.
✔️ Strong experience in supervised, unsupervised, and reinforcement learning techniques, model evaluation, and optimization.
✔️ Proficiency with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Keras, XGBoost, and Hugging Face.
✔️ Deep knowledge of data preprocessing, feature engineering, data augmentation, and building high-quality training datasets.
✔️ Ability to implement and fine-tune deep learning architectures such as CNNs, RNNs, LSTMs, GANs, and Transformers.
✔️ Experience with deploying ML models into production environments using MLOps tools and practices (e.g., MLflow, Kubeflow, TensorFlow Serving, SageMaker).
✔️ Strong programming skills in Python (preferred) and familiarity with Java, C++, or R for AI/ML development.
✔️ Expertise in natural language processing (NLP), computer vision (CV), recommendation systems, or time-series forecasting is a plus.
✔️ Ability to leverage cloud platforms (AWS, Azure, GCP) for scalable AI/ML solutions, including serverless architectures.
✔️ Knowledge of big data ecosystems (Spark, Hadoop) and experience handling large-scale datasets for training and inference.
✔️ Ability to perform model interpretability, bias detection, fairness evaluation, and responsible AI practices.
✔️ Experience in optimizing model performance, hyperparameter tuning, and deploying lightweight models for edge computing.
✔️ Strong skills in research, experimentation, and staying up-to-date with the latest AI/ML advancements and publications.
✔️ Ability to collaborate with data scientists, engineers, and product teams to understand requirements and deliver intelligent solutions.
✔️ Languages: English proficiency (additional language skills are a plus).