Senior AI/ML Engineer- NLP/Python

Senior AI/ML Engineer

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 model evaluation techniques.
• Implement AI-driven solutions using

  TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face

  , and similar frameworks.
• Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction.
• Deploy models in cloud environments (

  AWS, Azure, or GCP

  ) using SageMaker, Vertex AI, or Azure ML.
• Collaborate with cross-functional teams to integrate AI models into production systems.
• Ensure scalability, performance, and efficiency of AI/ML solutions.
• Stay updated with emerging AI trends and technologies to drive innovation.

Skills Required:

• Strong experience in

  machine learning, deep learning, NLP

  , and AI model development.
• Proficiency in

  Python, TensorFlow, PyTorch

  , and

  Scikit-learn

  .
• Expertise in

  NLP techniques

  (Word2Vec, BERT, transformers, LLMs, text classification).
• Hands-on experience with

  computer vision

  (CNNs, OpenCV, YOLO, custom object detection models) is a plus.
• Solid understanding of

  ML model deployment and MLOps

  (Docker, Kubernetes, CI/CD for ML models).
• Experience in working with

  cloud platforms

  (AWS, Azure, GCP) for AI/ML model deployment.
• Strong knowledge of

  SQL, NoSQL databases

  , and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc.).
• Familiarity with API development using Django, Flask, or FastAPI for AI solutions.
• Strong problem-solving, analytical, and communication skills.
• Experience with AI-powered chatbots,

  OpenAI API integration

  , and exposure to

  LLMs

  (GPT, LLaMA, Falcon, etc.) for real-world applications is a plus.
• Hands-on experience in generative AI models is a plus.

QUALIFICATION:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.