AI MLEngineer

AI/ML Engineer

About the Role

We are looking for a talented AI/ML Engineer to design, develop, and deploy intelligent systems and data-driven solutions. The ideal candidate will have a strong background in machine learning, deep learning, and data science, with hands-on experience in building scalable AI models for real-world applications.

Key Responsibilities

• Design, implement, and optimize machine learning models for classification, prediction, recommendation, or NLP tasks.
• Develop and deploy AI solutions across various platforms and environments (cloud, on-premises, edge).
• Preprocess and analyze large datasets for training and evaluation.
• Collaborate with data engineers, data scientists, and software developers to integrate AI models into production.
• Evaluate model performance, tune hyperparameters, and ensure scalability.
• Research and implement state-of-the-art algorithms and emerging techniques in AI and ML.
• Document processes, models, and results to ensure reproducibility and transparency.

Required Skills and Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or related field.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas).
• Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Knowledge of statistics, probability, and mathematical modeling.
• Experience with version control (Git) and collaborative development workflows.
• Familiarity with cloud platforms (AWS, GCP, Azure) and ML services (SageMaker, Vertex AI, Azure ML).

Preferred Qualifications

• Experience with deep learning (CNNs, RNNs, Transformers, LLMs).
• Familiarity with NLP, computer vision, or generative AI techniques.
• Experience with MLOps tools (MLflow, Kubeflow, DVC).
• Knowledge of data pipelines and big data technologies (Spark, Hadoop).
• Prior experience deploying models in production environments (APIs, containers, microservices).
• Contributions to open-source AI/ML projects or published research papers.