We are seeking an experienced Senior Data Scientist/Technical Lead/AI Researcher to join our team in developing state-of-the-art AI models tailored for applications in the energy industry.
This role offers a unique opportunity to apply advanced data science, machine learning, and engineering skills in a dynamic, collaborative startup environment. You will lead the end-to-end lifecycle of AI model development, from conceptualization through production, ensuring our solutions deliver measurable business value and align with industry demands.
Key Responsibilities:
Lead Development of NLP and Transformer Models: Design and optimize Natural Language Processing (NLP) models and transformer architectures for industry-specific applications, enabling intelligent processing of technical documents, reports, and unstructured data.
Speech-to-Text Research and Fine-Tuning: Conduct research and fine-tuning of speech-to-text models for local language and dialect applications, enhancing accuracy and usability in real-world scenarios. Integrate these capabilities into our local large language models (LLMs) for customized deployments.
Build and Scale Machine Learning Algorithms: Develop, deploy, and maintain machine learning models tailored to solve high-impact, real-world problems in the energy sector, ensuring models are robust, scalable, and maintainable.
Architect Data Pipelines and AI Infrastructure: Collaborate on the design of end-to-end data pipelines, APIs, and backend frameworks, ensuring data quality, consistency, and availability for AI applications.
Optimize Model Performance and Reliability: Focus on model optimization, tuning, and deployment strategies to enhance processing speed and reliability in production environments.
Drive Cross-Functional Collaboration: Partner closely with Engineering, AI, and Business teams to align technical solutions with business needs, leveraging insights for continuous improvement.
Qualifications:
Education: Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, or a related technical field.
Experience: Minimum 5 years in AI/ML/data science applications in production environment, with a proven track record in AI/ML model development, deployment, and maintenance. Previous experience in the energy or industrial sector is highly advantageous.
Analytical Mindset: Strong problem-solving skills and the ability to apply AI/ML solutions to complex technical problems in industrial applications.
GPU and Parallel Processing: Strong experience with GPU acceleration for deep learning, including CUDA programming, and experience with distributed computing frameworks (e.g., Dask, Spark) for parallel model training.
Technical Proficiency: Expertise in Python and proficiency in one or more additional languages (C#, Rust, etc.). Advanced understanding of NLP frameworks (Transformers, Hugging Face, etc.), machine learning libraries (TensorFlow, PyTorch), and data structures/algorithms.
Industry Insights: Enthusiasm for AI applications in the energy industry, with an understanding of how data science can drive business transformation.
Preferred Skills:
Technical Leadership: Proven experience leading technical teams in data science or AI/ML projects, with a strong ability to guide, mentor, and develop junior data scientists and engineers.
Strategic Vision: Ability to align technical objectives with business goals, making informed decisions that enhance both project impact and team productivity.
Project Management: Skilled in managing the AI/ML project lifecycle, from scoping and resource allocation to delivery and post-deployment monitoring.
Effective Communication: Strong ability to communicate complex technical concepts to both technical and non-technical stakeholders, ensuring transparency and alignment across departments.
Cross-Functional Collaboration: Demonstrated ability to work closely with product, engineering, and business teams to integrate AI solutions that meet strategic and operational needs.
What We Offer:
Impactful Work: Hands-on experience creating AI solutions with real-world applications in the energy industry.
Flexible Work Environment: Options for hybrid work with emphasis on deliverables.
Competitive Compensation: Competitive remuneration based on skills and experience.
About Us
AIngineer is at the forefront of driving digital transformation in heavy industries through innovative AI and data-driven solutions. Based in Kuala Lumpur, we are offering final-year and penultimate-year students an exciting opportunity to gain real-world industry experience. Join us as we tackle complex challenges and build scalable solutions to reshape the future of engineering and transform heavy industries.
Summary of role requirements:
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.