Sema Technical Due Diligence

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Machine Learning Scientist who will leverage Artificial Intelligence, Machine Learning, and Data Science to improve, transfer, and create innovative techniques for source code and software development analytics, with a focus on automated programming.

Tasks and Responsibilities

Sema is looking for a Machine Learning Scientist to assist with developing multimodal models which leverage various techniques and metrics in source code and software development. This scientist will be part of a multidisplinary team working to create first of kind methods that would improve the detection of poor software quality and process, as well as prediction, prevention, and correction of software quality issues.

Minimum Qualifications (Must have)

  • 2+ years of machine learning experience
  • MS in Computer Science, Statistics, Data Science or related field, or equivalent intensive training and accompanying portfolio
  • Strong proficiency and understanding of machine learning algorithms & principles, deep learning, probabilistic models, and Bayesian and statistical design
  • Strong proficiency with Python and high-performance computing
  • Experience with DL & ML libraries (tensorflow, keras, pytorch, sklearn)
  • Coding experience from inception through implementation in a production environment
  • Experience with cloud programming and architectures (AWS)
  • Solid understanding of good programming practices, architecture, design patterns and unit & e2e testing
  • Excellent communication and presentation skills
  • Known for passion and perseverance to pursue long-term goals through short-term high performance
  • Energized by driving innovative solutions and adapting quickly to new data
  • Demonstrate outstanding personal initiative and the ability to work effectively as part of a team
  • Desire to apply your skills in the service of a greater mission – fully automating the world’s software maintenance

Preferred Qualifications

  • Excellent software engineering skills in Python, Java, or C++
  • Domain experience in software analysis, parsers and grammars, and/or compilers
  • 2+ years experience working in Industry
  • Experience working with missing, time-series, high-dimensional, noisy, labeled, and sparse datasets
  • Experience working with graph traversal techniques, DAGs, and using ML & DL with graph data and graph networks
  • Experience running experimental ML and DL pipelines, hyper-parameter tuning, and training on large datasets
  • Experience in a start-up environment
  • Experience with causal and counterfactual inference

Working Conditions

  • Friendly, lively, remote, and multi-cultured
  • Work with a multidisciplinary team including software developers and architects, product designers, other DS/ML/DL scientists, and exceptional partners in industry and academia

Apply now