About the Company

Zebra Technologies fosters a collaborative environment where innovators unite to develop novel solutions that enhance everyday experiences. Driven by intellectual curiosity and a commitment to care, we engineer impactful solutions designed to proactively meet the evolving needs of our customers and partners, effectively addressing their most pressing challenges.

As a member of Zebra Nation, you will be recognized, respected, and valued for your contributions. Leveraging our diverse perspectives, we work together to achieve our shared objectives. This role offers the opportunity to join a team that is pushing the boundaries of innovation, redefining the future of work for organizations, their workforce, and the communities they serve.

At Zebra, you will have access to opportunities for professional growth and leadership within a forward-thinking organization. You can define a fulfilling career path while applying your skills to initiatives you are passionate about, both locally and globally. We are committed to continuous innovation – for our employees, our customers, and the global community.

Job Description

This position requires the design, development, programming, and implementation of machine learning solutions. The successful candidate will implement Artificial and Augmented Intelligence systems, Agentic Workflows, and Data Engineering Workflows. Statistical modeling and measurements will be performed by applying data engineering techniques, feature engineering, statistical methods, machine learning modeling, and AI techniques to structured, unstructured, and diverse “big data” sources of machine-acquired data. The aim is to generate actionable insights and foresights that can be applied to real-world business problem solutions and enhance product features and development.

Responsibilities

• Integrate cutting-edge machine learning algorithms and contribute to the development of innovative methodologies.
• Develop tools to facilitate the analysis and visualization of extensive datasets.
• Develop and code software programs to implement industry-standard automated machine learning models, including those for speech recognition, computer vision, text data processing, and Large Language Models (LLMs), statistical models, relevant machine learning models for device/machine-acquired data, and AI models and algorithms.
• Identify significant foresights based on predictive machine learning models derived from large data and metadata sources. Interpret and communicate these foresights, insights, and experimental findings to product managers, service managers, business partners, and business managers.
• Utilize rapid development tools, such as Business Intelligence tools, graphics libraries, and data modeling tools, to effectively communicate research findings through visual graphics, data models, machine learning model features, and feature engineering/transformations to relevant stakeholders.
• Analyze, review, and track trends and tools in the fields of data science, machine learning, artificial intelligence, and the Internet of Things (IoT).
• Collaborate with cross-functional teams to identify questions and issues related to data engineering and feature engineering for machine learning models.
• Evaluate and recommend improvements to data collection mechanisms to enhance the effectiveness of machine learning model predictions.
• Engage with customers, partners, product managers, and business leaders to present findings, predictions, and foresights. Gather customer-specific requirements for business problems and processes, and identify data collection constraints and alternatives for model implementation.
• Demonstrate working knowledge of MLOps, LLMs and Agentic AI/Workflows.
• Possess proficiency in Python programming and experience with machine learning frameworks such as TensorFlow and PyTorch.
• Exhibit hands-on experience in training, fine-tuning, and deploying LLMs.
• Maintain a strong understanding of open-weight LLM architectures, including training methodologies, fine-tuning techniques, hyperparameter optimization, and model distillation.
• Demonstrate a strong understanding of data engineering concepts, feature engineering, and workflow automation using Airflow or Kubeflow.
• Possess experience deploying machine learning models in cloud environments such as AWS, GCP (Google Vertex AI), or Azure using Docker and Kubernetes. Design and implement predictive and optimization models incorporating diverse data types.
• Exhibit strong proficiency in Python, Pyspark, and SQL.

Qualifications

• A bachelor’s degree, master’s degree, or Ph.D. in statistics, mathematics, computer science, or a related discipline is preferred.
• Possess 1-2 years of relevant experience.
• Demonstrate expertise in statistical modeling and algorithms.
• Exhibit experience in machine learning, including deep learning and neural networks, genetics algorithms, etc.
• Possess working knowledge of big data technologies such as Hadoop, Cassandra, and Spark R. Hands-on experience is preferred.
• Demonstrate proficiency in data mining.
• Exhibit proficiency in data visualization and visualization analysis tools, including R.
• Work or project experience in sensors, IoT, or the mobile industry is highly preferred.
• Possess excellent written and verbal communication skills.
• Be comfortable presenting to senior management and CxO-level executives.
• Be self-motivated and self-starting with a strong work ethic.

Skills

ATS Keywords

Frequently Asked Questions

Other Information

Work Arrangement: Hybrid
Travel Requirements (as a % of time): <10% Telework Availability: Yes, 70%. Requires visiting the Zebra site 2-3 days a week or every other week. Personal Protective Equipment (PPE) Required: No Physical Activities (all U.S. only jobs): Enter in N, O, F or C as applicable Enter in Frequency (N)Never, (O)Occasionally, (F)Frequently or (C)Constantly Ascending or descending ladders, stairs, scaffolding, ramps, poles and the like: N Working from heights such as roofs, ladders, or powered lifts: N Moving self in different positions to accomplish tasks in various environments including awkward or tight and confined spaces: N Remaining in a stationary position, often standing or sitting for prolonged periods: N Stooping, kneeling, bending, crouching, reaching, pushing/pulling: N Moving about to accomplish tasks or moving from one worksite to another: N Adjusting or moving objects up to __ pounds in all directions: N Communicating with others to exchange information: F Repeating motions that may include the wrists, hands and/or fingers: F (typing) Operating machinery and/or power tools: N Operating motor vehicles, industrial vehicles, or heavy equipment: N Assessing the accuracy, neatness and thoroughness of the work assigned: F Environmental Conditions (U.S. only): Enter in N, O, F or C as applicable Enter in Frequency (N)Never, (O)Occasionally, (F)Frequently or (C)Constantly Exposure to extreme temperatures (high or low): N Outdoor elements such as precipitation and wind: N Noisy environments: N Other hazardous conditions such as vibration, uneven ground surfaces, or dust & fumes: N Small and/or enclosed spaces: N No adverse environmental conditions expected: N Physical Demands (U.S. only): Check only one below Check only one below Sedentary work that primarily involves sitting/standing: X Light work that includes moving objects up to 20 pounds. Medium work that includes moving objects up to 50 pounds. Heavy work that includes moving objects up to 100 pounds or more (team lift) Must be able to see color.

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