Machine Learning Specialist

Applied Physics

$100K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or a similar technical field.
  • Experience in developing algorithms in areas like deep learning, natural language processing, and statistical modeling.
  • Proficient in programming languages such as Python, Java, Scala, or C/C++.
  • Familiarity with deep learning libraries like PyTorch, TensorFlow, or Keras.
  • Demonstrated ability to conduct original research and publish findings.
  • Experience working in multidisciplinary teams.
  • Strong verbal and written communication skills for effective collaboration.

Responsibilities

  • Conduct research on advanced Machine Learning algorithms.
  • Implement, train, and validate algorithms specific to various problem domains.
  • Integrate algorithms into larger programmatic systems.
  • Collaborate with a multidisciplinary team to achieve research objectives.
  • Engage in independent and collaborative research activities.
  • Publish results in peer-reviewed journals and present at conferences.
  • Travel to coordinate with collaborators and field sites as needed.

Benefits

  • Flexible work hours.
  • Opportunities for growth and career development.
  • Dynamic and passionate team environment.
  • Ability to make a positive impact on the world.
Full Job Description
In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields.

Responsibilities:
  • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
  • Implement, train, and validate proposed algorithms for specific problem domains.
  • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
  • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
  • Travel as required to coordinate research with collaborators and visit field sites.

Requirements
  • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
  • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
  • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
  • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
  • Proven ability to undertake original research and communicate findings in peer-reviewed publications.
  • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Benefits

We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world.

If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics.

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