Staff Machine Learning Engineer
Mozn -
Riyadh, Saudi ArabiaJob Details
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Job Description
About Mozn
Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it’s working to realise 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 the trusted AI technology partner for some of the largest government organizations, as well as many large corporations and startups.
We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity.
It is an exciting time to work in the field of AI to create a long-lasting impact.
About the role
We are seeking a talented hands-on Staff Machine Learning Engineer to lead one of ML Engineering teams at OSOS.
The ideal candidate is an Arabic speaker with a strong foundation in AI and machine learning, a record of building and deploying real-world AI systems.
As a Staff 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 the performance and latency of deployed models, responsible for inference and serving the pipelines, and maintaining ML infrastructure.
What you'll do
Leading a multidisciplinary team of ML engineers working on advanced Arabic language solutions and products
Designing, building, supporting, and scaling our cloud and/or our on-premise ML infrastructure
Deploying deep learning models in production environments and optimizing their performance for inference on either GPU or CPU
Maintaining our infrastructure (on-prem and cloud) and preparing it for training and inference purposes
Monitoring deployed ML models for their performance, latency, and throughput using automated tools for monitoring and reporting
Evaluating and improving data science processes, identifying opportunities for automation, efficiency, and scalability
Collaborating with other teams, including product managers, data scientists, software engineers, data annotators, and business stakeholders, to ensure successful deployments of ML models.
Guide the team in using best practices in ML engineering, software design, testing, versioning, and deployment for AI products
Staying up to date with the latest trends and advancements in ML engineering, ML models, and applying this knowledge to enhance the team’s capabilities
Exploring and learning new technologies that can complement or replace our current stack to improve it.
Ensure the team adopts modern ML tooling and infrastructure, including vector databases, orchestration tools, and scalable APIs
Proficiency in Arabic language is a must
Proficiency in one or more 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 with deploying Deep learning frameworks (e.g.
Tensorflow, Pytorch, Onnx) in production environments using inference frameworks (e.g.
Nvidia Triton, TFXServing, TorchServe)
Uphold 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, and/or promethues)
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
Experience managing remote or distributed teams
Benefits
Why Mozn?
You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
You will be given a lot of responsibility and trust.
We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it’s working to realise 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 the trusted AI technology partner for some of the largest government organizations, as well as many large corporations and startups.
We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity.
It is an exciting time to work in the field of AI to create a long-lasting impact.
About the role
We are seeking a talented hands-on Staff Machine Learning Engineer to lead one of ML Engineering teams at OSOS.
The ideal candidate is an Arabic speaker with a strong foundation in AI and machine learning, a record of building and deploying real-world AI systems.
As a Staff 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 the performance and latency of deployed models, responsible for inference and serving the pipelines, and maintaining ML infrastructure.
What you'll do
Leading a multidisciplinary team of ML engineers working on advanced Arabic language solutions and products
Designing, building, supporting, and scaling our cloud and/or our on-premise ML infrastructure
Deploying deep learning models in production environments and optimizing their performance for inference on either GPU or CPU
Maintaining our infrastructure (on-prem and cloud) and preparing it for training and inference purposes
Monitoring deployed ML models for their performance, latency, and throughput using automated tools for monitoring and reporting
Evaluating and improving data science processes, identifying opportunities for automation, efficiency, and scalability
Collaborating with other teams, including product managers, data scientists, software engineers, data annotators, and business stakeholders, to ensure successful deployments of ML models.
Guide the team in using best practices in ML engineering, software design, testing, versioning, and deployment for AI products
Staying up to date with the latest trends and advancements in ML engineering, ML models, and applying this knowledge to enhance the team’s capabilities
Exploring and learning new technologies that can complement or replace our current stack to improve it.
Ensure the team adopts modern ML tooling and infrastructure, including vector databases, orchestration tools, and scalable APIs
Proficiency in Arabic language is a must
Proficiency in one or more 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 with deploying Deep learning frameworks (e.g.
Tensorflow, Pytorch, Onnx) in production environments using inference frameworks (e.g.
Nvidia Triton, TFXServing, TorchServe)
Uphold 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, and/or promethues)
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
Experience managing remote or distributed teams
Benefits
Why Mozn?
You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
You will be given a lot of responsibility and trust.
We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
Job Requirements
Qualifications
Bachelor's or master's degree in computer science or a related field
+8 years of experience in a similar role
Proficiency with MLOps tools, CI/CD pipelines for ML, and scalable backend architecture
Bachelor's or master's degree in computer science or a related field
+8 years of experience in a similar role
Proficiency with MLOps tools, CI/CD pipelines for ML, and scalable backend architecture
