We are seeking a highly skilled Senior AI/ML Engineer with a specialization in NLP and Deep Learning. You will be responsible for designing, developing, and deploying end-to-end AI/ML models to solve complex business problems. This role requires extensive expertise in Python, key AI frameworks, and cloud-based AI solutions to ensure the scalability and performance of models in real-world applications.
Roles & Responsibilities:
- Design, develop, and deploy AI/ML models for real-world applications.
- Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems.
- Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment.
- Optimize model performance using hyperparameter tuning and various model evaluation techniques.
- Implement AI-driven solutions using frameworks like TensorFlow, PyTorch, Scikit-learn, and APIs from OpenAI or Hugging Face.
- Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction.
- Deploy models in cloud environments like AWS, Azure, or GCP using platforms such as SageMaker, Vertex AI, or Azure ML.
- Collaborate with cross-functional teams to integrate AI models into production systems.
Skills Required:
- Strong experience in machine learning, deep learning, and NLP.
- Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
- Expertise in NLP techniques such as Word2Vec, BERT, transformers, and LLMs.
- Hands-on experience with computer vision using tools like CNNs, OpenCV, and custom models.
- Solid understanding of MLOps, including deployment with Docker and Kubernetes.
- Experience with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment.
- Strong knowledge of SQL, NoSQL databases, and big data processing tools like PySpark and Databricks.
- Familiarity with API development using Django, Flask, or FastAPI for AI solutions.
- Strong problem-solving, analytical, and communication skills.
- Experience with AI-powered chatbots, LLMs, and generative AI models is a plus.
QUALIFICATION:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field, or equivalent practical experience.
