Responsibilities

Will have a strong background in machine learning and artificial intelligence with expertise in building and deploying AI-driven solutions.
Work closely with data scientists, software engineers and product teams to design, develop, and implement AI/ ML features that drive innovative Public Safety operations.
Evaluate model performance using appropriate metrics, and continuously improve models through hyperparameter tuning, cross-validation, and other techniques.
Deploy machine learning models into production environments, ensuring their scalability, reliability, and performance. Integrate AI models with existing systems and APIs.
Work closely with cross-functional teams (data scientists, engineers, product managers, and designers) to identify business problems and translate them into AI/ ML solutions.

Requirements

Degree in Computer Science or Information technology or equivalent.
2+ years of professional experience in AI/ ML engineering or a related field.
Prior experience as a project member of an AI/ ML implementation project.
Broad knowledge of current AI/ ML technologies such as Large Language Models (LLMs), Automatic Speech Recognition (ASR) and video analytics and how to incorporate said technologies into solutions across various domains.
Proficiency in programming languages such as Python, R, or Java.
Hands-on experience with popular machine learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn, Keras)
Strong knowledge of algorithms and data structures.
Familiarity with deep learning, reinforcement learning, computer vision, NLP, or other specialized AI domains.
Knowledge of SQL and data manipulation.
Experience with containerization and orchestration tools (Docker, Kubernetes) is a plus.
Strong analytical skills with the ability to translate complex problems into practical, scalable solutions.
Excellent written and verbal communication skills. Ability to explain complex technical concepts to non-technical stakeholders.
Able to work effectively in a collaborative, team-oriented environment.
Familiarity with agile development methodologies.