AI/ML Engineer
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Bangsar South, W.P. Kuala Lumpur

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Hybrid

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Direct hire

|Job ID 7803|Posted Jun 15, 2025
JOB DESCRIPTION
Job Title: AI/ML Engineer
Work Arrangement: Hybrid
Location: Kuala Lumpur, Malaysia
 
About Horizontal: Established since 2003 in the US, Horizontal solves complex challenges across two distinct businesses: Horizontal Digital and Horizontal Talent. We are consistently recognized for being a top workplace and one of the fastest growing private companies. Horizontal Talent specializes in staffing for IT, Digital & Creative and Business & Strategy markets. We have global offices in US, UAE, India, Malaysia and Australia.
 
Our Client is seeking a talented and exceptional Machine Learning Engineer who wants to make a difference in the world, has a strong drive for continuous learning and development, is open and collaborative, and never stops striving to improve themselves and the products or services they are responsible for. You will be responsible for developing and optimizing advanced machine learning (ML) models across various domains, including natural language processing (NLP), computer vision, and speech processing. This role requires broad expertise in large language models and diffusion models, with experience in ASR systems to support our comprehensive data analytics platform.

Key Responsibilities
  • Design, implement, and fine-tune Large Language Models (LLMs) for various NLP tasks, including text classification, entity extraction, sentiment analysis, and conversational AI applications.
  • Develop and optimize diffusion models for generating synthetic data, augmenting data, and creating multimodal content to enhance training datasets.
  • Build and maintain end-to-end machine learning pipelines for text processing, speech recognition, and multimodal data analysis.
  • Implement state-of-the-art transformer architectures and attention mechanisms for various sequence modeling tasks across different data modalities.
  • Research and integrate cutting-edge ML techniques, including few-shot learning, transfer learning, and multi-task learning approaches.
  • Collaborate with engineering teams to deploy ML models in production environments, ensuring scalability and reliability.
  • Develop custom training strategies, loss functions, and evaluation frameworks for domain-specific applications in telecommunications and government sectors.
  • Optimize model performance, inference speed, and resource utilization for deployment across various hardware configurations.
  • Conduct comprehensive model evaluation, A/B testing, and performance monitoring to ensure continuous improvement.
  • Create technical documentation, research reports, and best practice guidelines for ML development processes.
  • Mentor junior team members and contribute to the advancement of ML practices across the organization.

Required Qualifications
  • Advanced degree in Computer Science, Machine Learning, Data Science, Mathematics, or a related field.
  • 4+ years of experience in machine learning engineering with a focus on deep learning and neural networks.
  • Strong proficiency in Python and extensive experience with PyTorch, TensorFlow, and the HuggingFace ecosystem.
  • Demonstrated expertise with Large Language Models including GPT, BERT, T5, LLaMA, and similar transformer-based architectures.
  • Hands-on experience with diffusion models such as Stable Diffusion, DDPM, DDIM, or similar generative modeling techniques.
  • Experience with ASR (Automatic Speech Recognition) systems and speech processing pipelines, including models like Whisper, Wav2Vec2, or similar technologies.
  • Solid understanding of natural language processing techniques, including tokenization, embeddings, attention mechanisms, and sequence modeling.
  • Experience with parameter-efficient fine-tuning methods, including LoRA, QLoRA, AdaLoRA, and other PEFT techniques.
  • Knowledge of distributed training, model parallelism, and large-scale data processing frameworks.
  • Familiarity with MLOps practices, model deployment, and production monitoring systems.
  • Strong mathematical foundation in statistics, linear algebra, and optimization theory.
Technical Skills
  • Programming Languages: Expert-level Python; proficiency in C/C++, JavaScript, or Julia for performance optimization.
  • Deep Learning Frameworks: Advanced experience with PyTorch, TensorFlow, JAX, and HuggingFace Transformers.
  • LLM Technologies: Extensive knowledge of transformer architectures, attention mechanisms, tokenizers, and model scaling techniques.
  • Generative Models: Hands-on experience with diffusion models, VAEs, GANs, and other generative modeling approaches.
  • Fine-Tuning Techniques: Proficiency with LoRA, QLoRA, prefix tuning, prompt tuning, adapters, and instruction tuning methodologies.
  • NLP Libraries: Experience with spaCy, NLTK, Gensim, sentence-transformers, and domain-specific NLP tools.
  • Speech Processing: Familiarity with librosa, torchaudio, SpeechBrain, and audio processing pipelines.
  • Model Optimization: Knowledge of quantization, pruning, distillation, ONNX, TensorRT, and inference optimization.
  • Data Processing: Expertise in pandas, NumPy, Apache Spark, Dask, and distributed computing frameworks.
  • MLOps Tools: Experience with Docker, Kubernetes, MLflow, Weights & Biases, Ray, and cloud ML platforms.
  • Proficient in version control using Git, DVC, and collaborative ML development workflows.
Preferred Qualifications
  • Experience with multimodal learning combining text, audio, and visual data modalities.
  • Knowledge of reinforcement learning from human feedback (RLHF) and constitutional AI approaches.
  • Familiarity with federated learning and privacy-preserving machine learning techniques.
  • Experience with real-time inference systems and streaming data processing.
  • Understanding of model interpretability, explainable AI, and bias detection methodologies.
  • Knowledge of graph neural networks and knowledge graph embedding techniques.
  • Experience with AutoML frameworks and neural architecture search (NAS).
  • Contributions to open-source ML projects or published research in top-tier conferences.
  • Experience with edge deployment and mobile optimization for ML models.
  • Understanding of cybersecurity applications and adversarial machine learning.
Personal Attributes
  • Exceptional problem-solving skills and ability to approach complex ML challenges from first principles.
  • Strong research mindset with the ability to stay current with the rapidly evolving ML/AI landscape.
  • Excellent communication skills, both written and verbal, with the ability to explain complex concepts to diverse audiences.
  • Self-driven and proactive, with a passion for pushing the boundaries of machine learning technology.
  • Adaptable and open-minded, able to work effectively across different problem domains and data modalities.
  • Collaborative team player with experience working in cross-functional environments.
  • Strong attention to detail with commitment to reproducible and ethical AI practices.
Additional Information
  • Language: Fluent oral and written English is mandatory.
  • Good interpersonal skills
  • Excellent organizational skills
  • Team player but able to work on own initiative
  • Good written and oral communication skills
  • Enthusiastic, self-starter and highly self-motivated
  • Appreciation of cultural differences
  • Attention to detail
  • Travel: Occasional travel may be required for conferences, client meetings, or inter-office collaboration.
Horizontal is proud to be an Equal Opportunity and Affirmative Action Employer. 

We seek to provide employment opportunities to talented, qualified candidates regardless of race, color, sex/gender including gender identity and/or expression, national origin, religion, sexual orientation, disability, marital status, citizen status, veteran status, or any other protected classification under federal, state or local law.

In addition, Horizontal will provide reasonable accommodations for qualified individuals with disabilities. If you need to request a reasonable accommodation in order to complete the application or interview process, please contact us.

All applicants applying must be legally authorized to work in the country of employment.