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Selected role

Senior Applied ML Engineer (Speech Audio)

Nile Bits القاهرة, C, EG

Senior Full-time

Our recruitment is based on competencies or sets of behaviors, skills and knowledge and will focus on finding the best people for the available jobs. The selection process may involve several stages If you meet the requirements you will be required to attend an interview.

The interview will be about you and your experience. You will be asked for examples of how you behave in different situations drawing on examples from work, university or your personal life.

BENEFITS

All employees benefits for free (our famous games room, daily breakfast, fruits, coffee and other hot drinks, soft drinks and juices, company days out and parties…).
Flexible and comfortable schedule.
Social insurance.
Paid annual and national vacation.
Working remotely.
Competitive salaries.
Monetary rewards and incentives.
Career possibilities with growing team.
Open-door management policy.
Full Medical insurance.
Accommodation and transportation allowance.
Friendly environment that values innovation and efficiency.
Exciting opportunities for career growth and talent development.
Feedback encouragement.
Recognition and reward programs.
Friendly environment.
Fun committees.
Fun, smart and creative people.
Social benefits.

Equal Opportunity

Nile Bits is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

PRIVACY

Nile Bits respects your privacy and takes comprehensive measures to safeguard your personal and business information.

We will not share your credentials and business data with any third parties without your permission. Multi-level corporate security policies and procedures ensure prevention from loss, misuse or unauthorized distribution of any business-sensitive information you share with us.

Senior Applied ML Engineer (Speech & Audio)

*Employment Type: Fulltime

Job Location: Cairo, Egypt

Employee Location: Egypt

Work Arrangement: Remote

Project Overview**

Join a cutting-edge initiative focused on building advanced AI voice infrastructure for Arabic-speaking markets. The project involves developing state-of-the-art Arabic speech technologies, including:

Natural Text-to-Speech (TTS)
Real-Time Automatic Speech Recognition (ASR)
End-to-End Speech-to-Speech Conversational Systems

The solutions are tailored to regional Arabic dialects, including Egyptian, Gulf, Levantine, and others.

Job Description

We are seeking a highly skilled Senior Applied Machine Learning Engineer with deep expertise in speech and audio technologies. In this role, you will design, fine-tune, and optimize advanced machine learning models for Arabic voice applications. You will work across the full development lifecycle, from data pipeline construction and model experimentation to inference optimization and production deployment.

This position is ideal for engineers who are passionate about transforming cutting-edge research into scalable, low-latency systems that support natural and accurate Arabic speech interactions.

Key Responsibilities

Benchmark and evaluate TTS and ASR models using Arabic-specific test sets, measuring metrics such as Word Error Rate (WER), naturalness, and dialect coverage.
Fine-tune generative models for voice cloning, zero-shot speaker adaptation, and speech synthesis.
Build and maintain Arabic-focused data pipelines, including:
- Audio collection and preprocessing
- Diacritization (Tashkil)
- Data cleaning and augmentation
Optimize model inference for production environments using:
- Quantization
- KV-cache tuning
- Streaming inference techniques
Integrate and evaluate complete speech-to-speech conversational pipelines.
Conduct experiments based on recent research papers and convert findings into production-ready solutions.
Collaborate with engineering and product teams to deploy robust and scalable speech systems.

Required Qualifications

5+ years of experience in Machine Learning, Applied AI, or AI Research.
Strong programming skills in Python.
Extensive hands-on experience with PyTorch and the Hugging Face ecosystem.
Proven experience training and fine-tuning neural models for:
- Text-to-Speech (TTS)
- Automatic Speech Recognition (ASR)
- Audio codecs
Deep understanding of modern speech architectures such as:
- Whisper
- Conformer
- HiFi-GAN
- Diffusion-based models
Experience with audio processing techniques including:
- Voice Activity Detection (VAD)
- Speaker Diarization
- Neural Vocoders
Demonstrated ability to implement and adapt research papers into practical production experiments.
Strong understanding of Arabic language challenges, including:
- Diacritization (Tashkil)
- Dialectal variations
- Code-switching
Experience with inference optimization techniques such as:
- Quantization
- Streaming inference
- NVIDIA TensorRT

Preferred Qualifications

Experience developing custom NVIDIA CUDA kernels for high-performance model inference.
Familiarity with speculative decoding and other advanced acceleration techniques.
Experience deploying models at scale in cloud or GPU-based production environments.
Contributions to open-source speech or machine learning projects.

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