Data Scientist, Senior

Remote Work : Hybrid

Overview : At Zebra, we are a community of innovators who come together to create new ways of working to make everyday life better. United by curiosity and care, we develop dynamic solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being a part of Zebra Nation means being seen, heard, valued, and respected. Drawing from our diverse perspectives, we collaborate to deliver on our purpose. Here you are a part of a team pushing boundaries to redefine the work of tomorrow for organizations, their employees, and those they serve.

You have opportunities to learn and lead at a forward-thinking company, defining your path to a fulfilling career while channeling your skills toward causes that you care about – locally and globally. We’ve only begun reimaging the future – for our people, our customers, and the world.

Let’s create tomorrow together.

We are seeking a highly skilled and motivated Data Scientist (LLM Specialist) to join our AI / ML team. This role is ideal for an individual passionate about Large Language Models (LLMs) , workflow automation, and customer-centric AI solutions. You will be responsible for building robust ML pipelines , designing scalable workflows, interfacing with customers, and independently driving research and innovation in the evolving agentic AI space .

Key Responsibilities :

• LLM Development & Optimization : Train, fine-tune, evaluate, and deploy Large Language Models (LLMs) for various customer-facing applications.
• Pipeline & Workflow Development : Build scalable machine learning workflows and pipelines that facilitate efficient data ingestion, model training, and deployment.
• Model Evaluation & Performance Tuning : Implement best-in-class evaluation metrics to assess model performance, optimize for efficiency, and mitigate biases in LLM applications.
• Customer Engagement : Collaborate closely with customers to understand their needs, design AI-driven solutions , and iterate on models to enhance user experiences.
• Research & Innovation : Stay updated on the latest developments in LLMs, agentic AI , reinforcement learning with human feedback (RLHF), and generative AI applications. Recommend novel approaches to improve AI-based solutions.
• Infrastructure & Deployment : Work with MLOps tools to streamline deployment and serve models efficiently using cloud-based or on-premise architectures, including Google Vertex AI for model training, deployment, and inference.
• Foundational Model Training : Experience working with open-weight foundational models , leveraging pre-trained architectures, fine-tuning on domain-specific datasets, and optimizing models for performance and cost-efficiency.
• Cross-Functional Collaboration : Partner with engineering, product, and design teams to integrate LLM-based solutions into customer products seamlessly.
• Ethical AI Practices : Ensure responsible AI development by addressing concerns related to bias, safety, security, and interpretability in LLMs.

Responsibilities :

Qualifications :

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