Senior Data Scientist

About this opportunity:

Innovation & Incubation (AIII) unit in Santa Clara leads the charge in developing intelligent, autonomous network solutions. We are exploring agentic AI - AI agents that can sense, reason, and act independently - as a pathway to fully autonomous networks that self-optimize without human intervention. In this exciting role, you will leverage your expertise in transformer models, large language models (LLMs), and advanced ML to build AI-driven systems that push the boundaries of telecom network automation. If you are passionate about state-of-the-art AI (from open-source LLMs to time-series foundation models) and eager to apply it in a 5G/telecom context, this is the opportunity to drive innovation in a real-world, high-impact domain.

Ericsson Inc. does not sponsor US work authorizations for this job position including H-1B, O-1, and TN. Ericsson also does not hire F-1's working on EAD for this position.

What you will do:

• Lead AI Solution Development: Design, develop, and optimize advanced AI models leveraging large language models (LLMs), context engineering, knowledge graphs, advanced RAG techniques, and agentic AI systems to solve real-world telecom network problems. This includes fine-tuning transformer-based LLMs for domain-specific tasks and applying prompt engineering to refine their outputs.
• Autonomous Network Agents: Create and integrate intelligent AI agents capable of tool use and autonomous decision-making for network operations. You will develop multi-agent workflows that enable AI-driven closed-loop automation - allowing the network to monitor itself, evaluate solutions, and act on issues in real time.
• Time-Series Modeling: Apply cutting-edge time-series foundation models to telecom data for forecasting and anomaly detection. You will experiment with state-of-the-art architectures (e.g. Transformer-based models) to model temporal patterns in network KPIs and signals, helping predict issues before they arise.
• Prototype and Deploy Solutions: Work closely with telecom domain experts to define ML project objectives and develop algorithms that meet automation goals. Collaborate with software engineering teams to prototype and deploy your models into Ericsson's products for telco network operators, ensuring a seamless transition from proof-of-concept to production deployment. You will also enhance the reliability and scalability of these AI models in production environments.
• Innovate and Experiment: Explore new AI technologies and frameworks (e.g. new open-source LLMs, generative AI APIs, agent-based systems) that could improve network automation. You will stay up-to-date with the latest research in AI/ML and proactively bring in innovations - from novel agent evaluation methods to emerging AI tools - to continuously improve our solutions.
• Mentorship and Collaboration: Share your expertise by mentoring junior data scientists and fostering a culture of experimentation and knowledge-sharing. Work in a cross-functional setting, partnering with network engineers, data engineers, and product managers to ensure that AI solutions effectively address business needs and can be integrated smoothly into Ericsson's network management offerings.

• Experience & Education: 5-7 years of hands-on experience as a data scientist or AI/ML engineer, with a proven track record of delivering ML solutions end-to-end (from exploration to production). A Bachelor's degree in Computer Science, Data Science, Engineering or related field is required (Master's/Ph.D. preferred).
• ML/AI Expertise: Deep knowledge of machine learning fundamentals and neural network algorithms, including classic models and modern architectures. You should be well-versed in Transformer networks and NLP/LLM technologies, as well as other AI techniques like CNNs, RNNs, reinforcement learning, etc. Experience building and refining transformer-based LLMs (e.g., GPT-4, LLaMA, etc.) and familiarity with their open-source implementations and APIs is expected.
• Generative AI & Agents: Hands-on experience with state-of-the-art generative AI tools, fine tuning approaches such as LoRA/GRPO/SFT/RFT, knowledge of MCP and A2A, and platforms - including working with open-source LLMs and APIs (OpenAI, Anthropic, etc.). Knowledge of advanced RAG techniques, prompt engineering, and context engineering for improving LLM responses is highly valued. You should also understand advanced agentic AI concepts (e.g. the ReAct agent paradigm for decision-making) and have exposure to frameworks for building AI agents or autonomous workflows.
• Programming & Tools: Strong programming skills in Python and proficiency with the modern AI/ML ecosystem. This includes experience with deep learning frameworks (PyTorch, TensorFlow), NLP libraries (HuggingFace Transformers), and AI orchestration frameworks (such as LangGraph or similar) for tool integration. Familiarity with data science notebooks, version control, and MLOps tools for model deployment/monitoring is also important.
• Data Analytics & Foundations: Demonstrated ability to work with large, complex datasets (including time-series data). Experience in data preprocessing, feature engineering, and vector databases for embeddings is a plus. A solid foundation in mathematics, statistics, and probability is required to develop and validate models.
• Evaluation & Optimization: Experience in evaluating AI models and designing custom evaluation benchmarks to measure model/agent performance (e.g. testing for accuracy, bias, "hallucination" in LLM outputs, etc.). You continually iterate on models based on quantitative metrics and error analysis, and you are familiar with AI safety or reliability considerations in model development.
• Domain Knowledge: Basic understanding of telecommunications networks - including Radio access networks (RAN), Transport, and Core network domains. You have an interest in how AI can be applied to network optimization, operations, and automation; for instance, how AI-powered rApps (Radio apps) or agents can improve network performance and orchestrate resources autonomously. (Telecom/IoT domain knowledge is a strong plus.)
• Collaboration & Communication: Excellent problem-solving skills and ability to communicate complex AI concepts to cross-functional teams. You can effectively partner with business stakeholders and engineers, translating requirements into AI solutions and articulating results/insights clearly. Experience working in an agile, collaborative environment on innovative projects is preferred.
• Bonus Skills: Knowledge of Ericsson's product portfolio and solutions (for example, our network management tools, OSS/BSS systems, etc.) will greatly set you apart. Familiarity with industry standards (3GPP, O-RAN) and prior experience in network automation or telecom analytics projects is an advantage. Additionally, experience with AI data cloud platforms such as Snowflake and cloud platforms (AWS, Azure, GCP) for scalable ML would be beneficial.