Machine Learning Deep Learning

22 hours ago

Pune, Maharashtra, India Vittech Full time ₹ 8,00,000 - ₹ 12,00,000 per year

About the Role

We are seeking a passionate and skilled professional in Machine Learning, Deep Learning, and Data Science to join our growing team. The ideal candidate will work on building scalable AI/ML solutions, analyzing complex data, and contributing to innovative projects that drive business impact.

Key Responsibilities

  • Design, develop, and deploy machine learning and deep learning models for real-world applications.
  • Collect, preprocess, and analyze structured and unstructured data.
  • Build predictive and classification models, recommendation systems, and NLP/Computer Vision solutions.
  • Collaborate with cross-functional teams (Data Engineers, Software Developers, Product Managers) to integrate models into production.
  • Optimize model performance, scalability, and accuracy.
  • Stay updated with the latest research and advancements in AI/ML/DL.

Required Skills & Qualifications

  • Strong knowledge of Python and ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
  • Experience with deep learning architectures (CNNs, RNNs, Transformers, GANs, etc.).
  • Solid understanding of data structures, algorithms, and statistical methods.
  • Hands-on experience with data visualization tools (Matplotlib, Seaborn, Power BI/Tableau a plus).
  • Knowledge of cloud platforms (AWS, Azure, GCP) and deployment (Docker, Kubernetes) preferred.
  • Strong problem-solving skills and the ability to work in a fast-paced environment.
  • Bachelors/Masters degree in Computer Science, Data Science, AI, or related field.

Good to Have

  • Publications, research, or participation in Kaggle competitions.
  • Experience with big data tools (Hadoop, Spark).
  • Exposure to MLOps pipelines.

Perks & Benefits

  • Competitive salary and performance-based incentives
  • Exposure to cutting-edge AI/ML projects
  • Learning & development support (certifications, workshops, conferences)
  • Flexible work culture and collaborative team environmen

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