503 Neural Networks jobs in Malaysia

Job Summary:
The AI Development Team Lead is responsible for managing and mentoring a team of AI engineers, ML developers, and data scientists. This role bridges strategic objectives from the Head of Department (HOD) with execution by the technical team. The ideal candidate combines technical AI/ML expertise with project management and people leadership to ensure the successful delivery of AI initiatives that align with business goals.

Key Responsibilities:
Strategic Planning & Execution
• Collaborate with HOD to define AI vision, goals, and KPIs aligned with business needs.
• Translate high-level strategy into actionable technical tasks and sprint plans.
• Evaluate and recommend AI technologies, platforms, tools, and best practices.
Team Leadership & Management
• Lead, mentor, and manage a multidisciplinary team (AI engineers, ML specialists, data scientists).
• Conduct regular one-on-ones, performance reviews, and skill gap assessments.
• Promote a collaborative, transparent, and accountable team environment.
Technical Oversight
• Oversee design, development, testing, deployment, and maintenance of AI/ML models.
• Perform code reviews, model validation, and ensure adherence to engineering standards.
• Identify and resolve technical bottlenecks, support experimentation and innovation.
Project Management
• Manage project timelines, resource allocation, risk assessments, and reporting.
• Facilitate Agile ceremonies (sprint planning, stand-ups, retrospectives).
• Monitor and report on progress, blockers, and deliverables to HOD and stakeholders.
Cross-Functional Collaboration
• Work closely with product managers, data engineers, software teams, and business stakeholders.
• Ensure AI models and systems integrate well with broader platforms or customer touchpoints.
• Translate business questions into data science problems and actionable models.
Governance, Ethics & Compliance
• Ensure all AI/ML developments comply with data privacy laws and AI ethics standards.
• Define policies for model retraining, versioning, and explainability.

Qualifications & Skills:
Education:
• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Certifications in AI/ML (e.g., Google AI, AWS ML, Microsoft AI Engineer) are a plus.
Experience:
• 5–8 years total in AI/ML, with 2–3 years in a leadership or technical management role.
• Proven experience in deploying ML models into production (real-time or batch).
• Familiarity with Agile/Scrum practices and tools like Jira, Confluence, Git, etc.
Technical Proficiency:
• Proficient in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, etc.
• Experience with model lifecycle: training, tuning, deployment, and monitoring.
• Strong understanding of supervised/unsupervised learning, NLP, computer vision, or generative AI.
• Familiarity with MLOps: Docker, Kubernetes, MLFlow, CI/CD for AI pipelines.
• Experience working with cloud platforms: AWS, GCP, Azure.
Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong leadership, team-building, and conflict resolution skills.
• Analytical mindset with attention to both big-picture strategy and technicaldetail.

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Category: Information Systems & Technology

Posting Date: Mar 17, 2025

• Develop a prototype multi-agent chatbot system that can:
• Search and synthesize company information from public sources
• Analyze sales data and identify business opportunities
• Retrieve and analyze relevant internal documents
• Maintain context through multi-turn conversations

• Python programming
• Basic understanding of AI/ML concepts
• Strong analytical skills
• Self-motivated learner

Who we are? Arkema is a world leader in Innovative Materials for a Sustainable World with the ambition to become a pure Specialty Materials player.

We thrive as One Arkema , comprised of many businesses and brands including Bostik, ArrMaz, and more! and operating with a global reach in 55 countries with more than 21,100 employees. Each one contributes to positioning Arkema as a recognized leader of specialty chemicals and advanced materials, reporting annual sales of €9.5 billion, of which 2.9% allocated to R&D for 1,800 researchers in 17 R&D centers.

If you pursue excellence, love innovation and are inspired by challenges , we encourage you through to learn more about our values – Solidarity, Performance, Simplicity, Empowerment, and Inclusion – and how we concentrate on advances in bio-based and recyclable materials, new energies, water management, electronic solutions, lightweight materials and design, home efficiency and insulation.

Changing the world requires the right formula. The right formula consists of our innovative and sustainable materials, and you. Join us to develop the materials of tomorrow and make a difference together. What are you made of?

The legal information below pertains specifically to positions posted in the United States , however we strive for diversity, equity and inclusion in all the countries that we hire.

Arkema Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Arkema Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting and hiring.

• Assist in the research and development of AI-based learning materials for education and publishing.
• Support the team in designing, testing, and refining AI-generated content
• Work with supervisors to analyze data and evaluate AI-generated outputs for accuracy, quality, and usability.
• Contribute creative ideas to improve existing content development processes using AI tools.
• Assist in documentation and reporting of project progress, including compiling research findings and testing results.
• Collaborate with cross-functional teams (content creators, editors, designers) to ensure AI-generated material meets company standards.
• Perform other related tasks as assigned by the supervisor.

Job Type: Internship

Contract length: 3 months

Pay: RM RM600.00 per month

Work Location: In person

Job Summary:
The AI Development Team Lead is responsible for managing and mentoring a team of AI engineers, ML developers, and data scientists. This role bridges strategic objectives from the Head of Department (HOD) with execution by the technical team. The ideal candidate combines technical AI/ML expertise with project management and people leadership to ensure the successful delivery of AI initiatives that align with business goals.

Key Responsibilities:
Strategic Planning & Execution
• Collaborate with HOD to define AI vision, goals, and KPIs aligned with business needs.
• Translate high-level strategy into actionable technical tasks and sprint plans.
• Evaluate and recommend AI technologies, platforms, tools, and best practices.
Team Leadership & Management
• Lead, mentor, and manage a multidisciplinary team (AI engineers, ML specialists, data scientists).
• Conduct regular one-on-ones, performance reviews, and skill gap assessments.
• Promote a collaborative, transparent, and accountable team environment.
Technical Oversight
• Oversee design, development, testing, deployment, and maintenance of AI/ML models.
• Perform code reviews, model validation, and ensure adherence to engineering standards.
• Identify and resolve technical bottlenecks, support experimentation and innovation.
Project Management
• Manage project timelines, resource allocation, risk assessments, and reporting.
• Facilitate Agile ceremonies (sprint planning, stand-ups, retrospectives).
• Monitor and report on progress, blockers, and deliverables to HOD and stakeholders.
Cross-Functional Collaboration
• Work closely with product managers, data engineers, software teams, and business stakeholders.
• Ensure AI models and systems integrate well with broader platforms or customer touchpoints.
• Translate business questions into data science problems and actionable models.
Governance, Ethics & Compliance
• Ensure all AI/ML developments comply with data privacy laws and AI ethics standards.
• Define policies for model retraining, versioning, and explainability.

Qualifications & Skills:
Education:
• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Certifications in AI/ML (e.g., Google AI, AWS ML, Microsoft AI Engineer) are a plus.
Experience:
• 5–8 years total in AI/ML, with 2–3 years in a leadership or technical management role.
• Proven experience in deploying ML models into production (real-time or batch).
• Familiarity with Agile/Scrum practices and tools like Jira, Confluence, Git, etc.
Technical Proficiency:
• Proficient in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, etc.
• Experience with model lifecycle: training, tuning, deployment, and monitoring.
• Strong understanding of supervised/unsupervised learning, NLP, computer vision, or generative AI.
• Familiarity with MLOps: Docker, Kubernetes, MLFlow, CI/CD for AI pipelines.
• Experience working with cloud platforms: AWS, GCP, Azure.
Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong leadership, team-building, and conflict resolution skills.
• Analytical mindset with attention to both big-picture strategy and technicaldetail.

Job Summary:
The AI Development Team Lead is responsible for managing and mentoring a team of AI engineers, ML developers, and data scientists. This role bridges strategic objectives from the Head of Department (HOD) with execution by the technical team. The ideal candidate combines technical AI/ML expertise with project management and people leadership to ensure the successful delivery of AI initiatives that align with business goals.

Key Responsibilities:
Strategic Planning & Execution
• Collaborate with HOD to define AI vision, goals, and KPIs aligned with business needs.
• Translate high-level strategy into actionable technical tasks and sprint plans.
• Evaluate and recommend AI technologies, platforms, tools, and best practices.
Team Leadership & Management
• Lead, mentor, and manage a multidisciplinary team (AI engineers, ML specialists, data scientists).
• Conduct regular one-on-ones, performance reviews, and skill gap assessments.
• Promote a collaborative, transparent, and accountable team environment.
Technical Oversight
• Oversee design, development, testing, deployment, and maintenance of AI/ML models.
• Perform code reviews, model validation, and ensure adherence to engineering standards.
• Identify and resolve technical bottlenecks, support experimentation and innovation.
Project Management
• Manage project timelines, resource allocation, risk assessments, and reporting.
• Facilitate Agile ceremonies (sprint planning, stand-ups, retrospectives).
• Monitor and report on progress, blockers, and deliverables to HOD and stakeholders.
Cross-Functional Collaboration
• Work closely with product managers, data engineers, software teams, and business stakeholders.
• Ensure AI models and systems integrate well with broader platforms or customer touchpoints.
• Translate business questions into data science problems and actionable models.
Governance, Ethics & Compliance
• Ensure all AI/ML developments comply with data privacy laws and AI ethics standards.
• Define policies for model retraining, versioning, and explainability.

Qualifications & Skills:
Education:
• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Certifications in AI/ML (e.g., Google AI, AWS ML, Microsoft AI Engineer) are a plus.
Experience:
• 5–8 years total in AI/ML, with 2–3 years in a leadership or technical management role.
• Proven experience in deploying ML models into production (real-time or batch).
• Familiarity with Agile/Scrum practices and tools like Jira, Confluence, Git, etc.
Technical Proficiency:
• Proficient in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, etc.
• Experience with model lifecycle: training, tuning, deployment, and monitoring.
• Strong understanding of supervised/unsupervised learning, NLP, computer vision, or generative AI.
• Familiarity with MLOps: Docker, Kubernetes, MLFlow, CI/CD for AI pipelines.
• Experience working with cloud platforms: AWS, GCP, Azure.
Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong leadership, team-building, and conflict resolution skills.
• Analytical mindset with attention to both big-picture strategy and technicaldetail.