Machine Learning Engineer

3 weeks ago

Houston, Texas, United States Searce Inc Full time

About the Role:

As a Machine Learning Engineer at Searce Inc, you will be part of a dynamic team that develops and enhances the algorithms and technology that powers our unique system. This role covers a wide range of challenges, from developing new models using pre-existing components to enable current systems to be more intelligent.

Main Responsibilities:

  • Develop models that help achieve business objectives and track their progress using relevant metrics.
  • Manage available resources such as hardware, data, and personnel to ensure timely completion of projects.
  • Analyze ML algorithms to solve given problems and rank them by their success probability.
  • Explore and visualize data to gain insights and identify differences in data distribution that could affect model performance.
  • Verify data quality and ensure it via data cleaning and supervision of the data acquisition process if necessary.
  • Find available datasets online for training and define validation strategies.
  • Define preprocessing or feature engineering for a given dataset and data augmentation pipelines.
  • Train models and tune their hyperparameters, analyze errors, and design strategies to overcome them.
  • Deploy models to production and have knowledge and understanding of GCP Ecosystem.

Requirements:

  • BE/B.Tech/Masters in a quantitative field such as CS, EE, Information sciences, Statistics, Mathematics or related, with a focus on applied and foundational Machine Learning, AI, NLP and/or/data-driven statistical analysis & modeling.
  • 0-1 years of Experience majorly in applying AI/ML/NLP/deep learning / data-driven statistical analysis & modeling solutions to multiple domains, including financial engineering, financial processes a plus.
  • Strong, proven programming skills with machine learning and deep learning, and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop.
  • Experience with writing complex programs and implementing custom algorithms in these and other environments leveraging languages like Python, PySpark.
  • Experience beyond using open-source tools as-is, and writing custom code on top of, or in addition to, existing open-source frameworks.
  • Proven capability in demonstrating successful advanced technology solutions (either prototypes, POCs, well-cited research publications, and/or products) using ML/AI/NLP/data science in one or more domains.
  • Research and implement novel machine learning and statistical approaches.
  • Experience in data management, data analytics middleware, platforms, and infrastructure, cloud and fog computing is a plus.
  • Excellent communication skills (oral and written) to explain complex algorithms, and solutions to stakeholders across multiple disciplines, and ability to work in a diverse team.

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