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Title:  AI/ML Architect

Date:  26 Aug 2025
State:  Maharashtra
  • AI/ML Model Development:
    • Design, build, and deploy machine learning models and AI algorithms to address business challenges.
    • Develop and optimize deep learning models and algorithms to enhance performance and accuracy.
    • Implement algorithms for large-scale data processing and real-time analytics.
  • Deep Learning:
    • Design, implement, and optimize deep learning models for various applications, including classification, regression, and generative tasks.
    • Utilize frameworks such as TensorFlow and PyTorch to develop neural networks and advanced deep learning architectures.
  • Image Analytics:
    • Develop and deploy image recognition and analysis models to extract insights from visual data.
    • Apply convolutional neural networks (CNNs) and other image processing techniques to solve problems such as object detection, segmentation, and classification.
  • Video Analytics:
    • Implement video analysis solutions to process and interpret video data for tasks such as object tracking, action recognition, and anomaly detection.
    • Leverage deep learning techniques and tools for real-time video processing and analysis.
  • Voice Analytics:
    • Develop and deploy models for voice recognition, sentiment analysis, and speaker identification.
    • Use natural language processing (NLP) and audio signal processing techniques to analyze and interpret voice data.
  • Text Analytics:
    • Implement text mining and NLP techniques to extract valuable insights from unstructured text data.
    • Develop models for sentiment analysis, topic modeling, and text classification using state-of-the-art NLP frameworks.
  • Cloud & Infrastructure:
    • Utilize cloud platforms such as AWS and Azure for deploying and managing AI/ML models and infrastructure.
    • Leverage cloud-based tools and services, including Amazon SageMaker, Azure Machine Learning, and Azure Databricks, for model development and deployment.
  • Integration & Deployment:
    • Integrate AI/ML models into existing systems and workflows to ensure seamless operation.
    • Develop APIs and interfaces for model interaction and integration with applications.
  • Performance Monitoring:
    • Monitor and evaluate the performance of AI/ML models and systems to ensure they meet business objectives.
    • Continuously refine and optimize models based on performance data and feedback.
  • Collaboration:
    • Work closely with data scientists, business analysts, and other stakeholders to understand requirements and develop technical solutions.
    • Collaborate with cross-functional teams to implement and optimize AI/ML solutions.
  • Documentation & Reporting:
    • Maintain comprehensive documentation for AI/ML models, algorithms, and deployment processes.
    • Communicate technical findings and progress to stakeholders clearly and effectively.
  • Innovation & Best Practices:
    • Stay updated with the latest advancements in AI/ML technologies and techniques.
    • Explore and implement new tools and methods to enhance AI/ML capabilities and solutions.

Requirements:

  • Experience:
    • 5-7 years of hands-on experience in AI/ML engineering, including work with deep learning, image analytics, video analytics, voice analytics, and text analytics.
    • Proven track record of deploying machine learning models in production environments.
  • Technical Skills:
    • Proficiency in programming languages such as Python, R, or Java.
    • Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
    • Strong understanding of deep learning, image processing, video analytics, and NLP techniques.
  • Cloud Skills:
    • Hands-on experience with cloud platforms like AWS and Azure, including:
      • AWS: Amazon SageMaker, AWS Lambda, AWS Glue, Amazon Redshift.
      • Azure: Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure Cognitive Services.
  • Data Tools:
    • Experience with data visualization tools like Power BI, Tableau, or similar.
    • Familiarity with big data technologies and data storage solutions is a plus.
  • Soft Skills:
    • Strong analytical and problem-solving skills with attention to detail.
    • Excellent communication and interpersonal skills.
    • Ability to manage multiple projects and work in a fast-paced environment.
  • Educational Background:

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field with substantial experience in AI/ML engineering

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