Senior Mobile Product Designer - B2B, Ai-Driven

Les Mills Brasil ?

Auckland

On-site

NZD 90,000 - 102,000

Full time

3 days ago

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Job summary

Sentribee Limited in Auckland is seeking a Senior AI Engineer to design, develop, and maintain AI-powered software for enterprise use. The role covers machine learning, computer vision, data processing and the integration of cloud and edge computing.

You will lead complex AI projects, collaborate across teams, and ensure scalable, secure deployments while advancing proprietary AI technology. This is a permanent full-time position in Auckland.

Qualifications

Bachelor's degree in CS, SE or related field or 5+ years in AI/ML.
Strong Python with PyTorch/TensorFlow experience.
Experience designing AI architectures, APIs and scalable pipelines.

Responsibilities

Lead design and training of AI/ML models for business apps.
Develop CV solutions: object detection, tracking, classification.
Design scalable AI system architectures integrating edge and cloud.
Ensure performance, security and reliability.
Provide technical leadership and collaboration.

Skills

Bachelor's degree

AI engineering

Python

Machine learning

Computer vision

Edge computing

Cloud integration

Education

Bachelor's degree in CS/SE

Tools

PyTorch

TensorFlow

APIs

AWS/GCP

Job description

What Senior Mobile Product Designer B2b AI Dri...

Showing 1 Senior Mobile Product Designer B2b AI Driven jobs in Auckland

Auckland City Sentribee Limited

Posted 2 days ago

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Job Description

Job details:

Company: Sentribee Limited

Location: Auckland

Term: Permanent full time position

Wage: $65.00-$74.00 per hour

Hours of work: Minimum 30 hours per week, Maximum 40 hours per week, shifted by

roster from Monday to Friday

We are a company that aims to connect real-world observations, enterprise knowledge, AI agents, and business workflows to help organizations observe, understand, execute, and continuously improve operations.

We are currently seeking an accomplished Senior AI Engineer who is responsible for designing, developing, implementing and maintaining advanced AI-powered software applications and systems for the Employer's products and commercial projects. The role involves software engineering, AI system architecture, machine learning, computer vision, data processing, and the integration of cloud-based and edge computing technologies.

Requirements:

You must be well educated with at least a Bachelor's degree or higher qualification in computer science, software engineering or other related fields

Or have at least five years of relevant working experience in AI engineering, machine learning, computer vision or advanced software development.

Advanced proficiency in Python and widely used AI and machine-learning frameworks, including PyTorch, TensorFlow and related development tools.

Demonstrated ability to design and implement complex AI architectures, software systems, APIs and scalable inference pipelines.

Practical experience integrating AI technologies with cameras, sensors, IoT devices, edge computing platforms and cloud infrastructure.

Ability to independently lead technically complex development activities and solve challenging engineering problems.

Strong analytical, communication, documentation and cross-functional collaboration skills.

Commitment to information security, confidentiality, intellectual property protection and responsible AI development.

Duties and responsibilities:

1.Advanced AI and Machine Learning Development

Lead the design, development, training, evaluation and optimisation of advanced AI and machine-learning models for business and industry applications.
Develop sophisticated computer-vision solutions involving object detection, multi-object tracking, classification, recognition, segmentation, behavioural analysis and intelligent monitoring.
Research and implement advanced deep-learning architectures and algorithms to improve model accuracy, efficiency, reliability and performance.
Establish data preparation, annotation, model validation and benchmarking methodologies.
Identify technical limitations and develop innovative solutions to complex AI challenges.

2. AI System Architecture and Integration

Design and develop scalable AI system architectures integrating computer vision, sensors, edge devices, cloud infrastructure, APIs and enterprise software platforms.
Lead the development and optimisation of real-time and near-real-time AI inference pipelines.
Evaluate and select appropriate AI frameworks, computing infrastructure, hardware platforms and deployment technologies.
Develop reliable integration methods between AI models, cameras, IoT devices and distributed software systems.
Ensure AI solutions meet operational requirements for performance, scalability, maintainability and reliability.

3. Advanced Software Engineering

Design, develop and maintain complex software applications, APIs, backend services, AI processing pipelines and supporting development tools.
Establish and promote software engineering standards covering system architecture, code quality, version control, automated testing, logging and deployment.
Review technical designs and source code to maintain software quality, security and performance.
Diagnose and resolve complex software, algorithmic, infrastructure and integration issues.
Optimise system performance, resource utilisation and operational efficiency across edge and cloud environments.

4. Research, Innovation and Prototyping

Lead technical research and development activities involving emerging AI technologies, machine-learning methods and intelligent automation systems.
Design and implement experimental AI prototypes, proof-of-concept systems and technical validation projects.
Develop research methodologies, establish technical hypotheses, conduct experiments and evaluate results against defined performance objectives.
Identify opportunities for technological innovation and contribute to the development of proprietary AI technologies and intellectual property.
Prepare technical research reports, experimental records, performance evaluations and supporting documentation for R&D programmes and grant-related activities.

5. Technical Leadership and Project Delivery

Provide technical guidance, mentoring and support to AI engineers, software developers and other technical team members.
Contribute to technical project planning, architecture decisions, development priorities and implementation strategies.
Coordinate technical development activities to achieve agreed project milestones, quality standards and delivery objectives.
Identify technical risks, propose mitigation strategies and recommend appropriate engineering solutions.
Collaborate with management, researchers, suppliers and commercial partners to translate business requirements into practical technical solutions.

6. Data Management, Security and Intellectual Property

Establish appropriate technical practices for secure data processing, dataset management, model storage and access control.
Ensure AI systems and software development activities comply with the Employer's confidentiality, information security and data protection requirements.
Protect proprietary algorithms, source code, research findings, technical designs and other intellectual property.
Identify and address material security, privacy, data-quality and system integrity risks.

7. Deployment, Optimisation and Technical Support

Lead the deployment, testing, monitoring and performance optimisation of AI systems in development, pilot and commercial environments.
Develop strategies for reliable AI operation across cloud infrastructure, edge computing devices and field-based installations.
Investigate and resolve complex technical issues affecting model accuracy, system stability, latency and integration performance.
Evaluate operational feedback and implement continuous improvements to deployed AI solutions.
Provide advanced technical support and collaborate with customers, technology suppliers and research partners where authorised.

8. Technical Documentation and Collaboration

Develop and maintain comprehensive technical documentation covering AI models, datasets, system architecture, APIs, experiments, software components and deployment procedures.
Document technical decisions, research findings, testing outcomes and system improvements.
Communicate project progress, technical challenges, engineering risks and recommendations to management and relevant stakeholders.
Support knowledge sharing and technical capability development within the engineering team.

9. Other Duties