Deep Learning Engineer (Speaker Recognition)

42dot is developing advanced voice technology to enable more convenient communication for users in vehicles.
Pangyo-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea
Machine Learning
Mid-Level Software Engineer
Hybrid
2+ years of experience
AI · Automotive

Description For Deep Learning Engineer (Speaker Recognition)

42dot's Audio team is developing advanced voice technology to enable more convenient communication for users in vehicles. The Voice ID technology of the 42dot Audio team is a technology that recognizes the speaker's voice to provide personalized services. We are looking for talented individuals who will innovate in-vehicle experiences and open a new era of mobility through the development of Voice ID technology.

Responsibilities:

  • Design speaker recognition models
  • Evaluate the performance of speaker recognition models
  • Build speaker recognition databases
  • Develop and test speaker enrollment systems
  • Evaluate the performance of speaker enrollment systems

Qualifications:

  • At least 2 years of relevant experience (new graduates with a master's degree can apply)
  • Basic concepts/knowledge of voice signal processing
  • Research and development experience in the field of speaker recognition
  • Ability to use deep learning frameworks such as PyTorch

Preferred Qualifications:

  • Experience in commercialization/service related to speaker recognition
  • Project experience using reinforcement learning
  • Author of top-tier journal/conference papers in the fields of speaker recognition/speech recognition/machine learning/artificial intelligence

Interview Process:

  1. Document screening
  2. Coding test
  3. Video interview (about 1 hour)
  4. Face-to-face or video interview (about 3 hours)
  5. Final acceptance

The interview process may vary depending on the position and may change according to schedule and circumstances. The interview schedule and results will be individually notified via the email registered in your application.

Additional Information:

  • When submitting your resume, please exclude information prohibited by the Recruitment Procedure Act, such as resident registration number, family relationship, marital status, salary, photo, physical condition, and place of origin.
  • All submitted files should be uploaded in PDF format under 30MB.
  • After the interview process, a reputation check may be conducted with the applicant's consent.
  • Preference is given to national veterans and employment protection subjects in accordance with relevant laws.
  • Preference is given to persons with disabilities in accordance with the Act on the Promotion of Employment and Vocational Rehabilitation of Persons with Disabilities.
  • 42dot does not accept resumes from unsolicited search firms and does not pay fees for unsolicited resumes.

For more information about working at 42dot, please check:

  • 42dot Way: How 42dot works
  • Employee Engagement Program: 42dot's unique program to help employee engagement
Last updated 6 months ago

Responsibilities For Deep Learning Engineer (Speaker Recognition)

  • Design speaker recognition models
  • Evaluate the performance of speaker recognition models
  • Build speaker recognition databases
  • Develop and test speaker enrollment systems
  • Evaluate the performance of speaker enrollment systems

Requirements For Deep Learning Engineer (Speaker Recognition)

Python
  • At least 2 years of relevant experience (new graduates with a master's degree can apply)
  • Basic concepts/knowledge of voice signal processing
  • Research and development experience in the field of speaker recognition
  • Ability to use deep learning frameworks such as PyTorch

Benefits For Deep Learning Engineer (Speaker Recognition)

  • Employee Engagement Program

Interested in this job?

Jobs Related To 42dot Deep Learning Engineer (Speaker Recognition)

Java AI Developer

Java AI Developer position at Capco focusing on developing and optimizing AI-powered applications for financial services.

Developer Relations

Developer Relations role at Oumi, focusing on building and nurturing an open-source AI developer community through technical content creation, community engagement, and platform advocacy.

Machine Learning Engineer, Generative AI Innovation Center

Machine Learning Engineer role at AWS's Generative AI Innovation Center, focusing on LLM development, fine-tuning, and optimization for enterprise AI solutions.

Software Development Engineer, StoreGen

AI-focused Software Development Engineer role at Amazon, building next-generation development tools and practices using artificial intelligence.

Software Engineer- AI/ML, AWS Neuron Distributed Training

AWS Neuron seeks ML Engineer to develop distributed training solutions for cloud-scale machine learning accelerators, focusing on large language models and ML infrastructure.