We are seeking a talented Machine Learning Engineer to join our growing team. As a Machine Learning Engineer, you will play a pivotal role in optimizing ML models for efficient training and inference, deploying deep learning models in specialized hardware for inference usage, monitoring performance and latency of deployed models, and maintaining the ML infrastructure.
Mozn is a rapidly growing technology firm revolutionizing the field of Artificial Intelligence and Data Science, headquartered in Riyadh, Saudi Arabia. The organization aims to realize Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is a trusted AI technology partner for some of the largest government organizations, large corporations, and startups. The company is in an exciting stage of scaling to provide AI-powered products and solutions locally and globally.
What You'll Do:
- Design, build, support, and scale our cloud and/or on-premise ML infrastructure.
- Deploy deep learning models in production environments and optimize their performance for inference on GPU or CPU.
- Maintain infrastructure (on-prem and cloud) for training and inference purposes.
- Monitor deployed ML models for performance, latency, and throughput using automated tools.
- Evaluate and improve data science processes, identifying opportunities for automation, efficiency, and scalability.
- Collaborate with product managers, data scientists, software engineers, data annotators, and business stakeholders to ensure successful deployments of ML models.
- Stay informed on the latest trends and advancements in ML engineering and apply this knowledge to enhance the team’s capabilities.
- Explore and learn new technologies that can complement or replace the current stack.
Qualifications:
- Bachelor's or Master's degree in Computer Science or a related field.
- 2+ years of experience in a similar role.
- Proficiency in Arabic (Native Arabic speaker) is a must.
- Proficiency in programming languages (e.g., Python, C, C++) with the ability to learn new languages.
- Experience with relational databases, including SQL queries, database definition, and schema design.
- Experience deploying deep learning frameworks (e.g., TensorFlow, PyTorch, Onnx) in production environments using inference frameworks (e.g., Nvidia Triton, TFXServing, TorchServe).
- Familiarity with best practices and principles around clean code, version control, testing, continuous integration, and continuous deployment.
- Effective communication skills to convey technical solutions to end-users.
- Experience with monitoring ML models and reporting tools (e.g., Grafana, Prometheus).
- Experience with containerization technologies (e.g., Docker) is highly preferred.
- Experience with distributed computing systems is a plus.
- Experience with cloud platforms (e.g., AWS, GCP, OCI) is a plus.
- Knowledge of big data platforms like Kafka, Hadoop, and Spark is a plus.
Benefits:
- Competitive compensation and top-tier health insurance.
- An enabling culture that allows you to focus on your strengths.
- A fun and dynamic workplace with the opportunity to work alongside leading minds in AI.
- An inclusive environment that embraces diversity and empowers individuals to be their best selves.
