Ericsson

About this opportunity

As a Senior Machine Learning Engineer (SMLE), will be leading efforts for AI model deployment at scale, involving edge interfacing, ML pipeline and design of supervising and alerting systems for ML models. A specialist software engineer with experience building large-scale systems and enjoys optimizing systems and evolving them.

What you will do:

• Lead analysis of ML-driven business needs and opportunities for Ericsson and strategic customers.
• Define model validation strategy and establish success criteria in data science terms.
• Architect and design data flow and machine learning model implementation for production deployment.
• Drive rapid development of minimum viable solutions and leverage existing and new data sources.
• Develop solutions using Generative AI and RAG approaches.
• Design near real-time streaming and batch applications, ensuring scalability and high availability.
• Conduct performance analysis, tuning, and apply best practices in architecture and design.
• Document solutions and support reviews; contribute to product roadmap and backlog governance.
• Manage system packaging, software versioning, and change management.
• Perform design and code reviews, focusing on security and functional requirements.
• Collaborate with product teams to integrate ML models into Ericsson offerings
• Advocate for new technologies within ML communities and mentor junior team members
• Build ML competency within Ericsson and contribute to cross-functional initiatives.

You will bring:

• Proficient in Python with strong programming skills in C++/Scala/Java.
• Demonstrated expertise in implementing diverse machine learning techniques.
• Skilled in using ML frameworks such as PyTorch, TensorFlow, and Spark ML.
• Experience designing cloud solutions on platforms like AWS, utilizing services like SageMaker, EKS, Bedrock, and Generative AI models.
• Expertise in containerization and Kubernetes in cloud environments.
• Familiarity with Generative AI models, RAG pipelines, and vector embeddings
• Competent in big data storage and retrieval strategies, including indexing and partitioning.
• Experience with big data technologies like Spark, Kafka, MongoDB, and Cassandra.
• Skilled in API design and development for AI/ML models
• Proven experience writing production-grade software
• Competence in Codebase repository management like Git and any CI/CD pipelines.
• Extensive experience in model development and life-cycle-management in one or more industry/application domain
• Understanding and application of Security: Authentication and Authorization methods, SSL/TLS, Network Security (Firewall, NSG rules, Virtual Network, Subnet, Private Endpoint etc), Data Privacy handling and protection.
• Degree in Computer Science, Data Science, AI, Machine Learning, Electrical Engineering, or related fields from a reputable institution (Bachelor's, Master's, or Ph.D.)
• 10+ years of overall industry experience with 5+ years of experience in AI/ML domain