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▷ [13 / 10 / 2025] AIML Engineer

▷ [13 / 10 / 2025] AIML Engineer

Enterprise Minds, IncIndia
19 days ago
Job description

We’re looking for a highly skilled AI / ML Engineer to design, develop, and deploy advanced machine learning solutions that solve complex business challenges. You’ll work closely with cross-functional teams—Data Engineers, Product Managers, and Software Developers—to bring AI-powered features and insights into production-ready systems.

Key Responsibilities

  • Design & Develop ML Models : Build, train, and optimize machine learning and deep learning models for real-world applications (e.g., NLP, computer vision, recommendation systems).
  • Data Preparation & Feature Engineering : Collect, clean, and preprocess large-scale datasets for model development.
  • Deployment & Integration : Package models into APIs or services, deploy to cloud platforms (AWS, Azure, GCP), and ensure scalability and reliability.
  • Monitor & Maintain Models : Track model performance in production, retrain as needed, and manage version control.
  • Collaboration : Partner with product and engineering teams to translate business requirements into technical solutions.
  • Innovation : Research and implement cutting-edge ML algorithms and tools to improve existing processes and products.

Required Skills & Experience

  • 5–8 years of experience in AI / ML development and deployment.
  • Proficiency in Python (pandas, NumPy, scikit-learn) and at least one deep learning framework (TensorFlow or PyTorch).
  • Strong understanding of algorithms, statistics, and machine learning techniques (e.g., regression, classification, clustering, CNNs, RNNs).
  • Experience with cloud platforms (AWS SageMaker, Azure ML, or GCP AI Platform).
  • Familiarity with data engineering concepts (ETL, data pipelines, SQL / NoSQL databases).
  • Hands-on experience deploying ML models in production environments (e.g., REST APIs, Docker, Kubernetes).
  • Solid problem-solving skills and the ability to work in an agile, fast-paced environment.
  • Preferred Qualifications

  • Exposure to MLOps practices (CI / CD for ML, model monitoring, automated retraining).
  • Experience with natural language processing (NLP) or computer vision projects.
  • Knowledge of big data tools like Spark or Hadoop.
  • Master’s degree in Computer Science, Data Science, or a related field.
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