Machine Learning Engineer

1 week ago

Yelahanka, Karnataka, India GeekSoft Consulting Full time ₹ 12,00,000 - ₹ 36,00,000 per year
  • Help design, build and continuously improve the clients online platform
  • Research, suggest and implement new technology solutions following best practices/standards
  • Take responsibility for the resiliency and availability of different products
  • Be a productive member of the team.


Requirements
  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
  • 3+ years of hands-on experience in machine learning (ML) development.
  • Proficiency in one or more key ML domains and frameworks, including:
  • Supervised learning (e.g., classification, regression)
  • Unsupervised learning (e.g., clustering, anomaly detection)
  • Time-series analysis
  • Natural Language Processing (NLP)
  • Computer Vision (CV)
  • Statistical modeling
  • Demonstrated ability to select, implement, and adapt ML models to address real-world business problems.
  • Practical experience delivering data science and ML solutions in production environments.
  • Strong understanding of the ML lifecycle, including:
  • Data cleaning and preprocessing
  • Feature engineering
  • Model training and optimization
  • Performance evaluation and tuning
  • Proficiency in Python and common data science libraries such as Pandas, NumPy, Scikit-learn, etc.
Preferred Qualifications
  • Demonstrated expertise in deep learning.
  • Experience working with cloud data platforms, such as Databricks, AWS, or similar.
  • Familiarity with MLOps practices and tools for model deployment, monitoring, and automation.
  • Hands-on experience with PySpark and the Databricks platform.
  • Passion for continuous learning; stays current with the latest developments in ML and AI.
  • Bonus: Participation in Kaggle competitions and familiarity with industry benchmarks such as MLEBench.


Benefits
  • A challenging, innovating environment.
  • Opportunities for learning where needed.

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