AI Innovator

3 days ago

Pune, Maharashtra, India beBeeArtificialIntelligence Full time US$ 90,000 - US$ 1,20,000

Job Description

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  • Develop innovative AI and ML solutions for real-world applications, leveraging expertise in NLP, deep learning, and traditional ML algorithms to drive business growth.
  • Design, implement, and deploy end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment, ensuring scalability, performance, and efficiency of AI/ML solutions.
  • Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction, utilizing skills in computer vision (CNNs, OpenCV, YOLO, custom object detection models) and SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc.).
  • Collaborate with cross-functional teams to integrate AI models into production systems, ensuring seamless integration and high-quality delivery.

Required Skills and Qualifications

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  • Strong experience in machine learning, deep learning, NLP, and AI model development, with proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models.
  • Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification), as well as hands-on experience with generative AI models.
  • Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models), with experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment.
  • Strong problem-solving, analytical, and communication skills, with the ability to work effectively in a team environment.

Benefits

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  • Opportunity to work on cutting-edge AI and ML projects, driving innovation and business growth.
  • Collaborative and dynamic work environment, with opportunities for professional growth and development.
  • Competitive compensation and benefits package.

Others

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  • Stay updated with emerging AI trends and technologies to drive innovation.
  • Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks.
  • Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML.

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