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