AI Engineer

18 Minutes ago • 3 Years +
Research Development

Job Description

Seeking an experienced AI Engineer to develop and optimize a core AI-powered data processing service. This role involves leveraging Large Language Models (LLMs) to parse, normalize, and structure data from diverse sources into a consistent schema. Responsibilities include model training, fine-tuning, deployment, and performance enhancement, working closely with the software team for seamless integration and maintaining high accuracy and scalability.
Good To Have:
  • Experience with cloud platforms, especially Azure or AWS (Bedrock).
  • Hands-on experience with container orchestration using Kubernetes.
  • A strong understanding of microservice architecture principles.
  • Familiarity with MLOps tools and best practices.
Must Have:
  • Fine-tune and train LLMs using extensive datasets to improve accuracy, speed, and cost-efficiency.
  • Design and implement improvements to the existing API service, focusing on performance, scalability, and reliability.
  • Manage the end-to-end lifecycle of AI models, including data preprocessing, training, evaluation, deployment, and monitoring.
  • Work with models deployed in various environments, including self-hosted Docker containers and cloud-based services like AWS Bedrock or Azure OpenAI.
  • Collaborate with software engineers to ensure AI components are seamlessly integrated into microservices architecture.
  • Troubleshoot and resolve issues related to model performance, data parsing accuracy, and API operational health.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Minimum 5 years of professional experience in software development.
  • Minimum 3 years of hands-on commercial experience in an AI/ML engineering role.
  • Proven experience training and fine-tuning LLMs for specific NLP tasks (data extraction, classification, normalization).
  • Strong proficiency in Python and common AI/ML frameworks (PyTorch, TensorFlow, Hugging Face).
  • Experience deploying machine learning models into production environments.
  • Practical experience with containerization technologies, specifically Docker.
  • Solid understanding of API design and development (e.g., REST).

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Company Overview

​At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that’s critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future.

Department Overview

Motorola Solutions has recently acquired RapidDeploy Inc., and we’re excited to welcome new talent to our growing team. By applying for this role, you’ll become part of the RapidDeploy team within the broader Motorola Solutions organization—where innovation meets impact in the world of Public Safety.

At RapidDeploy, our mission is to reduce emergency response times by equipping dispatchers and call-takers with real-time situational awareness through advanced tactical mapping, and by delivering powerful analytics to help public safety agencies optimize their operations. Now, together with Motorola Solutions, we’re accelerating our shared vision of creating safer communities through smarter technology.

Job Description

We are seeking an experienced AI Engineer to take a key role in the development and optimization of our core AI-powered data processing service. This system leverages a Large Language Model (LLM) to parse, normalize, and structure data from highly varied sources into a consistent, pre-defined schema.

You will be responsible for the entire lifecycle of the model at the heart of this system—from training and fine-tuning to deployment and ongoing performance enhancement. You will work closely with our existing software team to ensure seamless integration and maintain the high performance and accuracy our clients depend on.

Key Responsibilities

  • Model Training & Optimization: Fine-tune and train LLMs using our extensive datasets of input and existing output data to continually improve accuracy, speed, and cost-efficiency.
  • System Enhancement: Design and implement improvements to the existing API service, focusing on performance, scalability, and reliability.
  • Lifecycle Management: Manage the end-to-end lifecycle of the AI models, including data preprocessing, training, evaluation, deployment, and monitoring.
  • Deployment: Work with models deployed in various environments, including self-hosted Docker containers and cloud-based services like AWS Bedrock or Azure OpenAI.
  • Collaboration: Collaborate with software engineers to ensure the AI components are seamlessly integrated into our microservices architecture and meet the required service-level objectives.

Maintenance & Support: Troubleshoot and resolve issues related to model performance, data parsing accuracy, and the API's operational health.

Basic Requirements

  • A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • A minimum of 5 years of professional experience in software development.
  • A minimum of 3 years of hands-on commercial experience in an AI/ML engineering role.
  • Proven experience training and fine-tuning Large Language Models (LLMs) for specific Natural Language Processing (NLP) tasks, such as data extraction, classification, and normalization.
  • Strong proficiency in Python and common AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
  • Experience deploying machine learning models into production environments.
  • Practical experience with containerization technologies, specifically Docker.
  • Solid understanding of API design and development (e.g., REST).

Advantageous Skills (Bonus Points)

  • Experience with cloud platforms, especially Azure or AWS (Bedrock).
  • Hands-on experience with container orchestration using Kubernetes.
  • A strong understanding of microservice architecture principles.
  • Familiarity with MLOps tools and best practices.

#LI-WC1

Travel Requirements

None

Relocation Provided

None

Position Type

Experienced

Referral Payment Plan

Yes

EEO Statement

Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.

We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

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