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
