Research Engineer

2 weeks ago

Gurugram, India ETS India Full time

Job Locations: Hyderabad, Telangana & Gurugram, Haryana


POSITION SUMMARY (the reasons the position exists; a summary of what the is position is responsible for):

Assist in the implementation of natural language processing (NLP) components of medium- to large-scale, complex research projects for ETS researchers, testing program areas, and external clients. Consult with research scientists in the application, modification, and documentation of such systems using established technologies.


PRIMARY RESPONSIBILITIES (indicate 5-10 key responsibilities/tasks that effectively describe the position; List from most important to least important):


  • Analyze, design, modify, develop, document and implement technologies for executing medium- to large-scale, complex NLP research and development tasks.
  • Identify and recommend solutions to unexpected problems in the application of NLP tools, and develop solutions.
  • Contribute to the implementation and support of new NLP methodologies to support research system development.
  • Assist in the preparation of NLP development components of proposals and cost/resource estimates.
  • Implement components of technical documentation of NLP software systems, solutions and results.
  • Maintain continuing awareness of recent advances in natural language processing (including speech processing), machine learning, and software development methodologies and leverage this awareness into creative solutions for ETS applications.


CRITICALITY -

  • The Research Engineer provides scientific and technical skills and leadership in the field of natural language processing.
  • This is an important role supporting the conceptualization and development of new automated scoring capabilities.
  • Moderate levels of risk, accountability and responsibility are associated with this role as it is supervised and works in conjunction with senior staff members.
  • Failure in this role will result in a delay departmental goals


Process Outputs and Deliverables (From the key responsibilities above, describe the most important process outputs of the role)

  • Input into design decisions for NLP research and development tasks and projects
  • Technical documentation for new and systems and solutions.
  • Solutions identified and recommended for NLP tools and applications
  • Input into NLP development components of proposals and cost/resource estimates


COMPLEXITY - (Describe the level of difficulty in the role; i.e. clearly defined processes vs. ambiguity; multiple stakeholder interests; undefined matrix relationships vs. defined hierarchical relationships)

  • The Associate Research Engineer, NLP works with moderately complex research projects and activities.
  • Most processes are defined, but individual research may be ambiguous and calls for sound judgement, Subject Matter Expertise and ingenuity.
  • Stakeholders include R&D staff, Assessment Development/Statistical Analysis and other SBUs throughout ETS, visiting researchers and collaborators and contractors for special service.


INTERDEPENDENCE – (Describe the involvement and level where the outputs are dependent on others, upstream and/or downstream)

  • The Automated Scoring and Natural Language Processing group is dependent on the Associate Research Scientist, NLP for assistance with the creation of new or modified NLP theories, research and analytic procedures (upstream).
  • ETS divisions and clients depend on the Associate Research Scientist’s contribution to the development of automated scoring technologies(downstream).


EDUCATION AND EXPERIENCE -

  • A Master’s degree in Computer Science, NLP, Language Technology, Computational Linguistics, Linguistics or a closely related field is required.
  • 4 years of relevant experience required.


Other Requirements (Specialized skill sets, behavioral/technical):


  • A strong programming background, in languages such as Perl, Java, Python, and C, and facility with computational algorithms are essential. Coursework in statistics and experience in using machine learning toolkits are highly desirable.
  • Knowledge of UNIX and Windows computing environments.
  • Familiarity with UNIX tools, scripting languages, and tools for managing software projects.
  • Familiarity with recently-developed algorithms, methods and data structures to support the processing of speech and language data.
  • Excellent verbal and written communication.

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