Senior Software Engineer_AI-ML

Role Summary:

As a Senior Software Engineer, you will architect, implement, test and deploy AI/ML Services and Systems, enabling AI Applications Development and Production deployment with focus on scaling, monitoring and performance.

The MLOps Platform unit is designing, engineering, operating, and maintaining a core system that delivers AI/ML Services and Systems, 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/ML Platform covers infrastructure capacity and tools for all AI/ML project and system needs for Ericsson products to realize telecom AI/ML Use cases. 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 leader, functioning as an individual contributor, as well as leading others.

Key Responsibilities:

1. As Architect perform detailed studies providing technical anatomy with estimates, implementation architecture/solution proposal,
2. As a Cloud Native – Micro Service Architecture based developer be proficient in languages like Python, Go, Java with applications deployed in containers on Kubernetes.
3. Develop/integrate/automate a core AI/ML software environment, in close collaboration with data scientist and product developers
4. 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.
5. 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
6. Evaluate and plan capacity of CPU, GPU, memory, storage, and networking resources to balance cost versus desired productivity and performance
7. Develop essential Pipelines for CI/CD, Test automation scripts and tooling to help short release cycles, quality assurance, maintenance, migration, and cost-control of infrastructure deployments.
8. Manage communication, planning, collaboration and feedback loops with business stakeholders.
9. Model the business problem statement into AI/ML problem.
10. Contribute to IPR creation for Ericsson in AI/ML
11. Lead functional and technical analysis within Ericsson businesses and for strategic customers to understand ML-driven business needs and opportunities
12. 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.
13. Provide ML Competence build-up in Ericsson Businesses and Customer Serving Units
14. Develop new and apply/extend existing, concepts, methodologies, techniques for cross functional initiatives

Key Qualifications:

1. Bachelors/Masters in Computer Science, Electrical Engineering or related disciplines from any of the reputed institutes. First Class, preferably with Distinction.
2. Applied experience: 5+ years of experience with infrastructure, platforms, networking, and software systems; 3+ years of experience with leading teams of engineers and system administrators; and an overall industry experience of about 10+ years.
3. Strong software engineering experience with one or more of Go, Python, Java using container-based Cloud Native – Micro Service development practices.
4. Certified Kubernetes Application Developer (CKAD) is desirable
5. Experience with data analytics and AI/ML systems, for example, Spark, Jupyter, Tensorflow
6. Experience with large scale systems, for example reliability/HA, deployment, operations, testing, and trouble-shooting.
7. Experience with delivering software products, for example release management, documentation
8. 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.
9. Experience with modern distributed systems and tooling, for example, Prometheus, Terraform, Kubernetes, Helm, Vault, CI/CD systems.
10. Experience with WAN networking solutions, redundancy/fail-over, QoS, and VPN technologies.
11. Strong system administration skills, Linux and Windows
12. Awareness of ITIL/ITSM methodologies for operations and service delivery

Soft Skills:

1. Good communication skills in written and spoken English
2. Great Team worker and collaborator
3. Creativity and ability to formulate problems and solve them independently
4. Self-driven and ability to work through abstraction
5. Ability to build and nurture internal and external communities
6. Ability to work independently with high energy, enthusiasm to learn and deliver with persistence