Machine Learning Engineer

4 days ago

Delhi NCR, India Codefeast Full time ₹ 1,04,000 - ₹ 1,30,878 per year

What does day-to-day look like:

  • Develop and maintain DS/ML solutions, including data pipelines, model training, evaluation, and optimization.
  • Collaborate with business stakeholders to gather and clarify requirements
  • Translate business requirements into DS/ML code that accurately reflects business logic
  • Write efficient, maintainable, and well-documented DS/ML solutions
  • Participate in code reviews and follow established development standards
  • Effectively analyze and select the best algorithms, optimize DS/ML solutions for performance improvement and accuracy
  • Create and maintain technical documentation for developed solutions
  • Support testing activities and resolve data-related issues

Required Qualifications:

  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
  • 5+ years of hands-on DS/ML development experience

  • Proficiency in at least some of the DS/ML areas and frameworks, including:

  • Supervised learning (classification, regression, )

  • Unsupervised learning (clustering, anomaly detection, )
  • Time-series analysis
  • Natural Language Processing (NLP)
  • Computer Vision (CV)

  • Statistical modeling

  • Ability to understand and apply different models to real-world use cases

  • Hands-on experience with DS and ML solutions in production environments
  • Strong understanding of data cleaning and wrangling, feature engineering, model optimization, and evaluation metrics
  • Proficiency in Python and its common data science libraries (e.g., Pandas, NumPy, Scikit-learn)
  • Strong knowledge of data analysis pipelines and data visualization techniques
  • Experience translating business requirements into DS/ML solutions

Preferred Qualifications:

  • Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
  • Experience with cloud data platforms (Databricks, AWS, etc.)
  • Knowledge of MLOps principles and tools for model deployment and monitoring
  • Hands-on experience with PySpark and Databricks Platform
  • Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
  • Bonus: Experience and knowledge in Kaggle competitions and Benchmarks, such as MLEBench

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