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

Based in Bengaluru, India, the AI Scientist will be a hands-on technical contributor responsible for designing, developing, and deploying state-of-the-art machine learning models that power Motorola Solutions’ mission-critical security and public safety products. This role requires deep technical acumen in specific AI domains, focusing on translating research into scalable, high-performance production systems. The AI Scientist will be a core member of our central AI organization, contributing directly to the foundational models and algorithms consumed by downstream product teams.


Key Responsibilities

The AI Scientist will be responsible for the research, development, and delivery of AI/ML models across the following core areas:
Model Research & Development: Conduct end-to-end development of AI/ML models from initial concept and literature review through to production deployment and monitoring.
Data Lifecycle Management: Collaborate with data engineering teams on large-scale dataset creation, annotation, quality control, and pipeline optimization to ensure high-quality training data.
Algorithm Optimization: Focus on optimizing model performance for real-time and edge deployment constraints, including latency, throughput, and computational efficiency.
Specialized AI Focus in at one of or more of the following areas:
Voice AI/Natural Language Processing: Evaluate, adapt and/or train robust speech recognition, translation, natural language understanding, and audio understanding models tailored for noisy, real-world public safety and security environments.
Computer Vision & Video Analytics: Develop and enhance models for complex object detection, tracking, re-identification, video search capabilities, and scene understanding from diverse video sources.
Foundational Model Fine-Tuning: Evaluate, fine-tune, and adapt large pre-trained and foundational models (e.g., LLMs, large vision models) for specific security-focused tasks and domain-specific knowledge integration.
Collaboration: Partner with software engineers to integrate models into the enterprise-scale cloud and edge AI platforms, ensuring reliability and scalability.
Evaluation & Validation: Establish rigorous, metric-driven evaluation frameworks (e.g., Precision, Recall, F1-Score) to benchmark model performance and drive continuous improvement on quantifiable customer outcomes.

Job Description

The AI Research Engineer  will be responsible for the research, development, and delivery of AI/ML models across the following core areas:

• Model Research & Development: Conduct end-to-end development of AI/ML models from initial concept and literature review through to production deployment and monitoring.

• Data Lifecycle Management: Collaborate with data engineering teams on large-scale dataset creation, annotation, quality control, and pipeline optimization to ensure high-quality training data.

• Algorithm Optimization: Focus on optimizing model performance for real-time and edge deployment constraints, including latency, throughput, and computational efficiency.

• Specialized AI Focus in at one of or more of the following areas:

  • Voice AI/Natural Language Processing: Evaluate, adapt and/or train robust speech recognition, translation, natural language understanding, and audio understanding models tailored for noisy, real-world public safety and security environments.

  • Computer Vision & Video Analytics: Develop and enhance models for complex object detection, tracking, re-identification, video search capabilities, and scene understanding from diverse video sources.

• Foundational Model Fine-Tuning: Evaluate, fine-tune, and adapt large pre-trained and foundational models (e.g., LLMs, large vision models) for specific security-focused tasks and domain-specific knowledge integration.

• Collaboration: Partner with software engineers to integrate models into the enterprise-scale cloud and edge AI platforms, ensuring reliability and scalability.

Evaluation & Validation: Establish rigorous, metric-driven evaluation frameworks (e.g., Precision, Recall, F1-Score) to benchmark model performance and drive continuous improvement on quantifiable customer outcomes.

 

Qualifications & Experience

• Education & Experience:

  • Bachelor's degree in Computer Science, Engineering, or a related field with 3+ years of professional experience in developing and deploying AI/ML solutions; OR

  • Master’s degree in Computer Science, Engineering, or a related field with 1+ year of professional experience in developing and deploying AI/ML solutions.

• Technical Acumen: Deep theoretical and practical understanding of machine learning principles, statistical modeling, and modern deep learning frameworks (e.g., PyTorch, TensorFlow).

• Core ML Engineering Skills: Proven experience with the full ML lifecycle, including problem formulation, data preparation, model training, hyperparameter tuning, and productionization.

• Domain Expertise (Must have strong experience in at least one):

  • Voice AI: Experience building models for Automatic Speech Recognition (ASR), speaker diarization, voice biometrics, or keyword spotting, with an understanding of audio feature extraction and noise robustness.

  • Computer Vision: Experience with state-of-the-art computer vision architectures (e.g., CNNs, Transformers) for tasks such as object detection, semantic segmentation, and video processing, and familiarity with fine-tuning large vision models.

• Programming: Strong proficiency in Python and relevant data science libraries (e.g., NumPy, Pandas, scikit-learn).

Communication: Excellent oral and written communication skills to articulate complex technical ideas to engineering and product teams.

Basic Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field with 3+ years of professional experience in developing and deploying AI/ML solutions; OR

• Master’s degree in Computer Science, Engineering, or a related field with 1+ year of professional experience in developing and deploying AI/ML solutions.

Travel Requirements

Under 10%

Relocation Provided

None

Position Type

Experienced

Referral Payment Plan

No

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.