Senior Machine Learning Engineer

4 months ago


مصر, Egypt Ericsson Full time

**Long Description**:
**About this opportunity.**

We are now looking for a Senior ML/MLOps Engineer with Google Cloud Platform (GCP) Experience to manage the Life Cycle of ML solutions within Ericsson R&D Global Teams. You will be working closely with our platform/product as well as with researchers, enabling fast iterations and scalable ML solutions for existing and future products. Your role will include all ML Life Cycle Management activities related to shipping, deployment, monitoring, and retraining of cloud native ML products. We are organized in cross-functional multi-domain development teams in which we foster continuous improvement, innovation, and knowledge sharing.

For more information, please refer to AI & Cloud Egypt

**What you will do**:
Facilitate the development and deployment of proof-of-concept ML-based solutions; both on-premises and cloud providers.
Package and productize ML algorithms to be production-ready.
Communicate with data scientists and software engineers and ensure ML-models compatibility with the rest of the software stack.
Create and maintain technical documentation for machine learning infrastructure and workflows.
Design pipelines and use MLOps infrastructure to support ML systems at scale.
Implement versioning of machine learning datasets, models and tracking of experiments.
Design and implement automatic ML models re-training triggers and processes.
Work with DevOps team to deploy and manage infrastructure for machine learning services.

**You will bring**:

- Bachelor’s degree in computer science, engineering, or a related field.
- Minimum 10+ years of experience in software development.
- Minimum 5+ years of experience as an ML/MLOps Engineer.
- Fluency in Python is a MUST.
- Excellent general Software Engineering skills: maintainable code, testing, design principles, Object Oriented Programming.
- Proficiency in classic DevOps, CI/CD practices, and Test Automation is a MUST.
- Experience with handling deployments on Cloud Infrastructure with Docker and Kubernetes.
- Knowledge of Agile Software Development Methodologies.
- Strong skills in the use of current state-of-the-art machine learning frameworks such as Tensorflow, Keras, scikit-learn, Pytorch, etc.
- Experience with Python packaging.
- Proven experience in deploying machine learning models into a production environment.
- Proficiency with loading data from different data repositories: SQL Databases, Data Warehouses, and Data Lakes.
- Experience with at least two of the MLOps platforms: MLFlow, Kubeflow, KServe, Seldon, DVC, CometML, etc. is a MUST.
- Experience with KNative and serverless deployments is a strong plus.
- Experience with Cloud MLOps platforms (Vertex AI, SageMaker, etc...) is a plus.

**Data Related Skills**
- Working knowledge of message queuing, stream processing, and batch processing tools.
- Experience with Distributed computing frameworks (Spark, Dask, Ray)
- Experience with workload management and orchestration frameworks.

**Backend Related Skills**
- Experience with server-side programming and using APIs is a must.
- Experience with using at least one Python Web Framework is a must.
- User authentication and authorization between multiple systems, servers, and environments.

**Non-technical Skills**:

- Excellent oral and written communication skills.
- Excellent problem-solving and troubleshooting skills.
- Proactive & team player.

**Why join Ericsson?**

At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

**What happens once you apply?**

Click Here to find all you need to know about what our typical hiring process looks like.

**Primary country and city**: Egypt (EG) || location_obj

**Job details**: Developer



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