Grow with us

About this opportunity:

It will be practically impossible for human brains to understand how to run and optimize next generation of wireless networks, i.e., 5G networks with distributed edge compute, that will drive economic and social transformation for all aspects of society. Machine Learning (ML) and other Artificial Intelligence (AI) technologies will be vital for us to handle this opportunity. We are expanding the Ericsson MLOps Engineering Unit with tech savvy developers with right attitude and skillset.

MLOps is an iterative process for building, deploying, operationalizing, and observing AI/ML systems. MLOps aim is to manage the end-to-end life cycle of AI/ML models through all the phases, experimentation, development, deployment, model performance monitoring and re-training and, when needed, re-design and re-architecture to keep models operating in optimal conditions in production environments. A MLOps platform provides services and components to assist and guide organizations through this iterative process. MLOps platform components are designed to overcome the challenges to develop and operate AI/ML systems at industrial scale on production environments.

Role Summary

As a Software Engineer, you will build and deploy MLOps Services and components, enabling AI Use Cases Development and Production deployment with focus on scaling, monitoring and performance, re-using the MLOps Platform.

The MLOps Platform unit is designing, engineering, operating, and maintaining cloud native K8s based micro-service Architecture – Service and Components that delivers that aim to deliver end to end MLOps features and functionality e.g. CI/CD, data exploration notebooks (Jupyter), ML model development and deployment, workflow engines, and ML frameworks (i.e. TensorFlow) for easy consumption by Ericsson products and services.

The AI MLOps Platform covers infrastructure capacity and tools for all AI/ML project and system needs across different Ericsson Products. The main approach is to integrate/extend existing private and public cloud infrastructures, and to base the toolbox components on open source software. The deployed environments are heterogeneous, so multi-cloud, hybrid-cloud, and WAN networking are also key technology areas.

In this role, you are expected to be a very hands-on developer, functioning as an individual contributor, as well as work within a cross functional team that is responsible from study, design, implement, test, deliver and maintain phases of the projects/products.

Key Responsibilities

• Develop/integrate/automate a core AI/ML software environment, in close collaboration with data scientist and product developers
• Operationalize and extend open source software components, covering the entire ML model life-cycle, including e.g. data transformation, model development, deployment, monitoring, re-training, security.
• Collaborate with product development teams and partners in Ericsson Businesses to industrialize a platform for machine learning models and solutions as part of Ericsson offerings including providing code, workflows and documents
• Work with MLOps projects and development teams to identify needs and requirements for AI/ML tools and infrastructure resources.
• Evaluate and plan capacity of CPU, GPU, memory, storage, and networking resources to balance cost versus desired productivity and performance
• Develop essential automation scripts and tooling to help quality assurance, maintenance, migration, and cost-control of infrastructure deployments.
• Manage communication, planning, collaboration and feedback loops with business stakeholders.
• Model the business problem statement into AI/ML problem.
• Contribute to IPR creation for Ericsson in AI/ML
• Lead functional and technical analysis within Ericsson businesses and for strategic customers to understand MI-driven business needs and opportunities
• Lead studies and creative usage of new and/or existing data sources. Work with Data Architects to leverage existing data models and build new ones as needed.
• Provide MI Competence build-up in Ericsson Businesses and Customer Serving Units
• Develop new and apply/extend existing, concepts, methodologies, techniques for cross functional initiatives

Key Qualifications

• Bachelors/Masters in Computer Science, Electrical Engineering or related disciplines from any of the reputed institutes. First Class, preferably with Distinction.
• Applied experience: 2+ years of experience with infrastructure, platforms, networking, and software systems; and an overall industry experience of about 4+ years.
• Strong software engineering experience with one or more of Golang, Java, Scala, Python, JavaScript, using container-based development practices
• Experience with data analytics and AI/ML systems, for example, Spark, Jupyter, Tensorflow
• Experience with large scale systems, for example reliability/HA, deployment, operations, testing, and trouble-shooting.
• Experience with delivering software products, for example release management, documentation
• Experience with usage/integration of public cloud services, for example, identity and access management, key management, storage systems, CPU/GPU, private/virtual networking, and Kubernetes services.
• Experience with modern distributed systems and tooling, for example, Prometheus, Terraform, Kubernetes, Helm, Vault, CI/CD systems.
• Experience with WAN networking solutions, redundancy/fail-over, QoS, and VPN technologies.
• Experience with Infrastructure-as-code and SRE ways-of-working
• Strong system administration skills, Linux and Windows
• Awareness of ITIL/ITSM methodologies for operations and service delivery

Soft Skills

• Good communication skills in written and spoken English
• Great Team worker and collaborator
• Creativity and ability to formulate problems and solve them independently
• Self-driven and ability to work through abstraction
• Ability to build and nurture internal and external communities
• Ability to work independently with high energy, enthusiasm and persistence

Experience in partnering and collaborative co-creation, i.e., working with complex multiple stakeholder business units, global customers, technology and other ecosystem partners in a multi-culture, global matrix organization with sensitivity and persistence.