Machine Learning Engineer

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. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Department Overview

Our Analytics & AI R&D Center in Vietnam is a strategic innovation hub, dedicated to advancing the frontiers of Video Intelligence. We are transitioning from traditional computer vision to an "AI-First" approach, leveraging Foundation Models to solve critical real-world challenges in public safety.

Job Description

We are seeking a highly skilled Senior Machine Learning Engineer to act as a core Individual Contributor within our AI Engineering organization. In this high-impact role, you will take ownership of researching, designing, and developing cutting-edge Computer Vision algorithms to solve real-world public safety challenges.

Recognizing that modern AI encompasses vast and diverse domains, we offer high flexibility in this role. We do not expect candidates to be full-stack masters of every domain. Instead, we highly value deep specialization. We welcome candidates who possess profound, hands-on expertise in EITHER resource-constrained Edge inference optimization OR large-scale Cloud AI model development and algorithmic data mining.

Core Responsibilities

As a Senior Machine Learning Engineer, you will contribute heavily to core algorithm development while leveraging your specific strengths:

Core AI/ML Development:

• Design, train, and fine-tune high-performance deep learning models for complex vehicle attribute detection and optical character recognition (OCR) utilizing modern architectures (CNNs, Vision Transformers).

• Apply a Data-Centric AI approach, potentially leveraging Generative AI (Diffusion Models, GANs) for Synthetic Data Generation to overcome long-tail anomalies and obscured data in natural environments.

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Specialized Domain Focus (Depending on your primary expertise):

• If specializing in Edge AI: Rigorously profile trained models to identify latency bottlenecks. Apply advanced optimization techniques (INT8/FP16 quantization, pruning) and convert models for deployment via TensorRT, TFLite, or ONNX on embedded hardware (ARM CPUs, custom NPUs, low-power devices).

• If specializing in Cloud AI & Data Mining: Architect and develop advanced machine learning algorithms and AI pipelines to mine actionable insights from massive cloud-based datasets. Focus on large-scale model training, integrating Vision-Language Models (VLMs) for complex text-to-image retrieval, and optimizing deep learning architectures to process and extract intelligence from high volumes of unstructured video/image data.

• Write clean, highly efficient, well-documented, and maintainable production-level code (Python/C++).

Basic Requirements

Experience & Education:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Computer Vision, or a related technical field.

• 3+ years of rigorous professional experience in applied Machine Learning, Computer Vision, or AI Research/Development.

• Proven hands-on track record of transitioning models from research/prototypes into robust commercial production.

Technical Competencies:

• Deep practical mastery of AI frameworks, primarily PyTorch or TensorFlow.

• Strong programming proficiency in modern Python and/or C++ within Linux environments.

• Specialization Flexibility: Demonstrated deep expertise and practical achievement in AT LEAST ONE of the following domains:

  • Domain A (Edge AI): Hardware acceleration, edge model profiling, model compression, and deployment tools (TensorRT, TFLite, edge devices).

  • Domain B (Cloud AI & Data Mining): Deep expertise in large-scale AI model training, computer vision algorithms, and designing complex AI pipelines for handling massive datasets (e.g., extracting statistical patterns and intelligence from billions of records).

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Preferred:

• Familiarity with Multimodal Foundation Models (e.g., CLIP, LLaVA) for Open-Set Recognition or Text-to-Image retrieval.

• Experience in building Agentic workflows or automated Active Learning systems

Travel Requirements

Under 10%

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.