Senior Data Scientist - AI Model Optimization (LLM/SLM) for Network Automation

As the global leader in high-speed connectivity, Ciena is committed to a people-first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual growth, well-being, and belonging. We're a technology company that leads with our humanity-driving our business priorities alongside meaningful social, community, and societal impact.

We are seeking a highly skilled and innovative Data Scientist to join our team focused on revolutionizing network troubleshooting and operations. In this role, you will be responsible for adapting, shrinking, and specializing large, general-purpose AI models into highly efficient, domain-specific experts. Your work will directly contribute to creating Small Language Models (SLMs) and other distilled models that can be deployed in real-time or near-real-time environments to predict, diagnose, and resolve complex network issues.

You will be a key player in transforming raw network telemetry, alarms, logs, and trouble tickets into actionable intelligence, empowering Ciena's software platforms to achieve unprecedented levels of automation.

What You Will Do at Ciena

• Model Distillation & Compression:Design and implement knowledge distillation pipelines to transfer the capabilities of large "teacher" models (like foundational LLMs) into smaller, faster "student" models. The goal is to retain high accuracy while drastically reducing latency and computational cost for deployment in resource-constrained environments.
• Fine-Tuning Expertise:Fine-tune foundational language models (LLMs) using Ciena's vast and unique datasets, including network alarms, system logs, performance metrics, technical documentation, and historical trouble tickets. You will employ state-of-the-art techniques like instruction tuning and Parameter-Efficient Fine-Tuning (PEFT), including LoRA and QLoRA.
• Develop Specialized Small Language Models (SLMs):Create and train SLMs specifically for network troubleshooting tasks, such as:
  • Root Cause Analysis (RCA):Identifying the primary source of a network fault from a cascade of alarms.
  • Log Summarization:Condensing verbose syslog and event data into human-readable summaries.
  • Next-Best-Action Recommendation:Suggesting corrective actions or commands for network operators.
  • Anomaly Detection:Interpreting subtle deviations in network telemetry to predict future failures.
• Research & Application:Stay at the forefront of AI/ML research in model optimization, NLP, and time-series analysis. Evaluate and apply emerging techniques to solve complex networking challenges.
• Data-centric AI:Collaborate with network subject matter experts and data engineers to curate high-quality training datasets. Perform exploratory data analysis (EDA) and feature engineering on complex network data (e.g., optical performance metrics, routing protocol states, packet-level statistics).
• MLOps & Deployment:Work closely with software and MLOps engineers to package, containerize (e.g., Docker), and deploy your models within Ciena's automation platforms, like Blue Planet. Monitor model performance in production and establish pipelines for continuous retraining and improvement.

Who You Are (Required Qualifications)

• Master's degree or PhD in Computer Science, Electrical Engineering, Statistics, or a related quantitative field.
• 2+ years of hands-on experiencein a Data Scientist or Machine Learning Engineer role.
• Proven, practical experience with fine-tuning Large Language Models (LLMs). You can speak to the challenges and successes of adapting a model to a specific domain.
• Strong understanding of and hands-on experience with model compression techniques such as knowledge distillation, quantization, or pruning.
• Expert-level proficiency in Python and core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Deep experience with at least one major deep learning framework: PyTorch (preferred), TensorFlow, or JAX.
• Proficiency with the NLP ecosystem, particularly the Hugging Face stack (Transformers, PEFT, Datasets).

Desirable Skills & Experience

• Experience in the telecommunications or networking industry. Familiarity with network data sources like SNMP, syslog, gNMI/gRPC, IPFIX, and network alarms is a significant plus.
• Knowledge of multi-layer networking from optical (DWDM, OTN) to packet (L2 switching, L3 routing/IP/MPLS).
• Experience building and deploying models on cloud platforms (GCP Vertex AI, AWS SageMaker, Azure ML).
• Familiarity with MLOps tools and principles (e.g., MLflow, Kubeflow, CI/CD for models).
• Published research in top-tier AI/ML conferences or journals.
• A passion for solving real-world, high-impact problems and seeing your work transition from research to production.

Why Ciena?

• Impact:Your work will directly influence the reliability and performance of networks that billions of people rely on every day.
• Innovation:You'll be working on the cutting edge of applied AI with access to unique, large-scale datasets.
• Culture:We foster a collaborative, inclusive, and supportive environment where great ideas can thrive.
• Growth:Ciena provides extensive opportunities for learning and professional development.

If you are passionate about pushing the boundaries of what AI can do and want to apply your skills to solve tangible, complex challenges in the networking world, we encourage you to apply.

The salary range for this position is:

Canada: $81,600.00 - $130,400.00

USA:$91,000 - $145,400.00

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At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.

Ciena is anEqual Opportunity Employer, including disability and protected veteran status.

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