ML Engineer (STT, NMT, TTS)

TransPerfect; Uppsala; On-site; SEK 550 000 - 850 000; Full time

Job summary

TransPerfect seeks a Machine Learning Researcher with a focus on Speech-to-Text (STT), Neural Machine Translation (NMT), and Text-to-Speech (TTS) systems. The successful candidate will develop novel models and implement AI solutions, collaborating across teams. A Master's or Ph.D. in relevant fields along with strong proficiency in Python and deep learning frameworks is essential for this role.

Qualifications

• Experience with STT, NMT, TTS systems preferred.
• Familiarity with large language models like LLaMA, GPT.
• Experience deploying ML models to production environments.

Responsibilities

• Conduct research and development of novel models in STT, NMT, and TTS.
• Transition promising research into production-grade implementations.
• Collaborate with cross-functional teams including product and engineering.

Skills

Proficiency in Python

Deep Learning frameworks

Software engineering skills

Handling large datasets

Education

Master’s or Ph.D. in Computer Science

Equivalent industry experience in applied AI research

Tools

PyTorch

TensorFlow

C#

.NET

Azure

AWS

Job description

As a Machine Learning Researcher specializing in STT, NMT, and TTS systems, you will independently and collaboratively conduct research and development of novel models in these domains under the guidance of the Head of R&D. This role requires excellent technical skills and the ability to bring innovative AI solutions from research to robust, production-grade implementations.

RESPONSIBILITIES

• Conduct research and development of novel models in STT, NMT, and TTS, independently or in collaboration with other team members.
• Build and iterate on research prototypes, conducting experiments and evaluations.
• Transition promising research into robust, production-grade implementations.
• Work with cross-functional teams including product, engineering, and design to bring AI solutions to life.
• Stay up-to-date with the latest research in speech and language AI and adapt state-of-the-art ideas to our needs.

REQUIRED EXPERIENCE AND QUALIFICATIONS

• Master’s or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or a related field OR equivalent industry experience in applied AI research.
• Strong proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Solid understanding of machine learning and deep learning fundamentals.
• Hands-on experience with at least one of:

> Speech recognition models (e.g., experience with open-source toolkits such as Kaldi, DeepSpeech, or ESPnet, or designing and implementing a custom STT system).

> Neural Machine Translation with Transformer-based architectures (e.g., proficiency in frameworks like OpenNMT, Fairseq, or MarianNMT, or hands-on experience developing an end-to-end NMT system).

> Text-to-Speech systems (e.g., familiarity with models like Tacotron, FastSpeech, or WaveGlow, or building a complete TTS pipeline).

> Experience with training, fine-tuning, or adapting large language models such as LLaMA, GPT, Mixtral.

• Familiarity with handling large datasets and conducting rigorous evaluation of models.
• Strong software engineering skills, including experience with version control, modular code design, and working with complex codebases.

PREFERRED QUALIFICATIONS

• Experience deploying ML models to production environments (cloud or on-prem).
• Proficiency in C# and .NET (our broader platform is built in .NET technologies).
• Familiarity with Azure, AWS or other cloud platforms.
• Basic understanding of front-end technologies (e.g., HTML, JavaScript, and CSS) for prototyping demo interfaces.

DESIRED SKILLS AND EXPERIENCE

• Passionate about the intersection of AI research and real-world applications.
• Enjoy experimenting, learning, and iterating with limited specs or guidance.
• Clear and proactive communication with peers and stakeholders.
• Initiative and ownership, especially when navigating ambiguity.
• Openness to working with unfamiliar tools or domains when needed

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