Zebra Technologies

Remote Work: Hybrid

Overview:

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.

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

You'll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about – locally and globally.

Come make an impact every day at Zebra.

Data Scientist Lead:

Focuses on developing non-LLM models using classical ML techniques for prediction, anomaly detection, and trend analysis. Complements LLM engineers by building quantifiable models to support AI-first decisioning.

Responsibilities:

• Build, train, and validate ML models (e.g., regression, clustering, forecasting).
• Develop feature extraction pipelines from structured and unstructured data.
• Deep understanding of reinforcement learning algorithms, including recent advances like RLHF, DPO, PPO, and multi-agent systems.
• Experience in learning and service development using GPU: Experience in building GPU-based Training or Inference systems.
• LLM's Post-training related experience: Experience in utilizing Supervised Fine-Tuning and Parameter Efficient Fine-Tuning.

Skills Required:

• Proficient in Python, scikit-learn, and statistical modeling.
• Good understanding of model evaluation metrics (ROC, F1, RMSE).
• Exposure to MLflow or equivalent model management tools.

Qualifications:

Preferred Education: Bachelor's or Master’s degree in an appropriate

engineering discipline required.

Preferred Work Experience (years): Minimum of 8+ years of work experience or

5 years of relevant experience with a Master’s degree.

Key Skills and Competencies:

All other Regions:

Preferred Education: Bachelor’s degree

Preferred Work Experience (years): 8+ years of work experience

Required :

• Build, train, and validate ML models (e.g., regression, clustering, forecasting).
• Develop feature extraction pipelines from structured and unstructured data.
• Deep understanding of reinforcement learning algorithms, including recent advances like RLHF, DPO, PPO, and multi-agent systems.
• Experience in learning and service development using GPU: Experience in building GPU-based Training or Inference systems.
• LLM's Post-training related experience: Experience in utilizing Supervised Fine-Tuning and Parameter Efficient Fine-Tuning.

Skills Required:

• Proficient in Python, scikit-learn, and statistical modeling.
• Good understanding of model evaluation metrics (ROC, F1, RMSE).
• Exposure to MLflow or equivalent model management tools.

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.

Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy.