Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. We deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.  The actionable insights we deliver safeguard lives and protect critical assets around the worldBabel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K. For more information, visit www.babelstreet.com. 

We are seeking a highly skilled and motivated Senior Research Engineer with a strong background in natural language processing (NLP) and large language models to join our dynamic research team. The ideal candidate will have a deep understanding of NLP techniques, experience with large language models, and a proven track record of applying these skills to solve real-world problems. This role involves developing and implementing innovative solutions for event extraction, name matching, and other NLP applications. This will be a hybrid role working out of either our Somerville, MA or Tel Aviv offices.

Key Responsibilities: 

  • Work on research and development efforts in NLP and large language models to solve complex problems and create innovative solutions. 
  • Design, implement, and evaluate NLP systems for applications such as event extraction, name matching, domain adaptation, information extraction and more. 
  • Collaborate with cross-functional teams to integrate NLP technologies into our product. 
  • Publish research findings in journals and conferences, and contribute to the scientific community. 

Qualifications: 

  • Master’s degree in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field. PhD preferred. 
  • Strong background in NLP and experience with large language models (e.g., GPT, BERT, Transformer models). 
  • Proficient in programming languages such as Python and frameworks/libraries like TensorFlow, PyTorch, etc. 
  • Demonstrated ability to design and implement complex NLP systems from concept through production. 
  • Problem-solving skills and creativity in developing new algorithms and models. 
  • Excellent communication and collaboration skills. 

 

Benefits at Babel Street (just to name a few...)

  • Health Benefits: Babel Street covers 90-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances – for you and your family!
  • Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
  • Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
  • Holidays: Babel Street provides employees with 12 paid Federal Holidays
  • Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.

                   

Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their co‐worker, Pay Transparency Nondiscrimination. In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations.

 

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