We are seeking a motivated AI/ML Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning and artificial intelligence with expertise in building and deploying AI-driven solutions.
You will work closely with data scientists, software engineers and product teams to design, develop, and implement AI/ ML features that drive innovative Public Safety operations.
Responsibilities:
Model Evaluation & Optimization
Evaluate model performance using appropriate metrics, and continuously improve models through hyperparameter tuning, cross-validation, and other techniques.
Deployment & Integration
Deploy machine learning models into production environments, ensuring their scalability, reliability, and performance. Integrate AI models with existing systems and APIs.
Collaboration
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:
- 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.