The Role

We are looking for a hands-on Senior ML Engineer to lead the development and operation of production-grade AI systems across LLMs, OCR, and voice. This role combines deep technical ownership with leadership of a high-performing team of junior engineers, as well as direct engagement with stakeholders to shape AI solutions.

Responsibilities:

* Lead and mentor a team of highly talented junior ML engineers through:

* Code reviews, design reviews, and technical direction

* Enforcement of strong software engineering and ML best practices

* Design, deploy, and operate scalable AI systems with a focus on reliability and performance

* Lead production deployment of LLMs and multimodal systems (RAG, OCR, voice)

* Own **model performance end-to-end**, combining evaluation, observability, and hardware optimization:

* Build evaluation pipelines (benchmarks, regression testing, LLM-as-judge)

* Implement deep observability (tracing, latency, error tracking)

* Optimize GPU utilization (multi-GPU serving, batching, quantization, memory tuning)

* Continuously improve throughput, latency, and cost efficiency

* Architect and manage GPU infrastructure:

* Model serving, load balancing, and scaling strategies

* Hardware-aware deployment and performance tuning

* Build and maintain robust MLOps pipelines:

* Model/version management, CI/CD, automated testing, and rollback strategies

* Monitoring and feedback loops for continuous improvement

* Engage directly with clients and stakeholders to:

* Gather and clarify business requirements

* Translate non-technical needs into well-defined technical problems

* Communicate solutions, trade-offs, and progress through clear documentation, reports, and proposals

* Contribute hands-on to system design, implementation, debugging, and production incident resolution

* Proven experience deploying LLMs in production

* Strong experience with GPU-based inference and optimization

* Solid backend engineering skills (Python, APIs, distributed systems)

* Experience with MLOps and production ML systems

* Experience with OCR/document AI and/or voice systems (STT/TTS)

* Experience with Docker and Kubernetes

* Strong understanding of modern AI architectures (RAG, vector DBs, agent workflows)

* Experience mentoring or leading engineers

* Strong communication skills with the ability to bridge business and technical domains

Nice to Have:

* Experience with open-weight models (Qwen, Llama, DeepSeek, Gemma)

* Experience with on-prem / sovereign AI deployments

* Experience with LoRA / fine-tuning

* Multilingual or Arabic NLP experience

PhazeRo remote jobs

Senior Machine Learning Engineer / Technical Lead