Service Planner & Data Analyst: Bi & Insights Champion

Daikin New Zealand; Auckland; On-site; NZD 90,000 - 102,000; Full time

Job summary

Sentribee Limited in Auckland seeks a Senior AI Engineer to design, develop and maintain AI-powered software for our products and projects. You will lead AI architectures and scalable inference pipelines across edge and cloud platforms.

Ideal candidates have a degree in CS/SE or 5+ years in AI engineering, strong Python, PyTorch and TensorFlow skills, and a track record of collaboration across teams.

Experience with sensors, IoT, data processing, security and responsible AI practices is a plus.

Qualifications

• Bachelor's degree in computer science, software engineering or related field.
• 5+ years in AI engineering, ML, CV or advanced software development.
• Advanced proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
• Experience designing complex AI architectures, APIs and scalable inference pipelines.
• Experience with cameras, sensors, IoT, edge and cloud platforms.

Responsibilities

• Lead the design, development, training, evaluation and optimisation of AI models.
• Develop computer-vision solutions: detection, tracking, classification, recognition, segmentation.
• Design scalable AI architectures integrating vision, sensors, edge, cloud, APIs.
• Lead deployment, monitoring and optimisation of AI systems across environments.
• Provide technical leadership and mentoring to engineers.

Skills

Python

AI

Machine learning

Computer vision

APIs

Edge computing

Education

Bachelor's degree or higher in CS/Software Engineering

Tools

PyTorch

TensorFlow

Python

Job description

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

• Perform other lawful and reasonable duties consistent with the seniority, technical expertise, capability and responsibilities of the position.

Applicants for this position should have NZ residency or a valid NZ work visa.

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