Job Description

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

.

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.

Programming Skills:

Proficiency in

Python

and experience with ML frameworks like

TensorFlow, PyTorch

LLM Expertise:

Hands-on experience in training, fine-tuning, and deploying LLMs (e.g., OpenAI's GPT, Meta's LLaMA, Mistral, or other transformer-based architectures).

Foundational Model Knowledge:

Strong understanding of

open-weight LLM architectures

, including

training methodologies, fine-tuning techniques, hyperparameter optimization, and model distillation

.

Data Pipeline Development:

Strong understanding of

data engineering concepts

, feature engineering, and workflow automation using

Airflow or Kubeflow

.

Cloud & MLOps:

Experience deploying ML models in cloud environments like

AWS, GCP (Google Vertex AI), or Azure

using

Docker and Kubernetes

.

Model Serving & Optimization:

Proficiency in

model quantization, pruning, distillation, and knowledge distillation

to improve deployment efficiency and scalability.

Research & Problem-Solving:

Ability to conduct

independent research

, explore

novel solutions

, and implement state-of-the-art ML techniques.

Strong Communication Skills:

Ability to

translate technical concepts

into actionable insights for non-technical stakeholders.

Version Control & Collaboration:

Proficiency in

Git, CI/CD pipelines

, and working in

cross-functional teams

.

Qualifications:

Bachelor's degree. Advanced degree-masters or PhD-strongly preferred in Statistics, Mathematics, Data / Computer Science or related discipline 2-5 years experience Statistics modeling and algorithms Machine Learning Experience-including deep learning and neural networks, genetics algorithm etc. Working knowledge Big Data-Hadoop, Cassandra,Spark R. Hands-on experience preferred Data Mining Data Visualization and visualization and analysis tools including R Work/Project experience in sensors, IoT, mobile industry highly preferred Excellent verbal and written communication Comfortable with presenting to senior management and CxO level executives Self motivated and self starter with high degree of work ethic


To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.