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Principal Machine Learning Engineer

2 weeks, 1 day ago
Singapore
Full-time
Lead
Machine Learning Engineer
Software Development
Apache Spark Deep Learning Machine Learning PyTorch
Apply Now
AVOMIND

AVOMIND

AVOMIND is a global recruitment firm based in Berlin, specializing in hiring commercial, strategy, and analytics & insights talent for companies and candidates worldwide. With a focus on executive search and embedded recruitment, AVOMIND connects high-...

Professional Services
11-50
Founded 2019
View All Jobs 106

Description

  • Build and own end-to-end machine learning pipelines from data processing through training, evaluation, inference, and deployment.
  • Fine-tune and adapt models using modern techniques such as LoRA, QLoRA, SFT, DPO, and model distillation.
  • Design and operate scalable inference systems while balancing latency, cost, and reliability.
  • Develop and maintain data pipelines for synthetic and real-world training datasets.
  • Build evaluation frameworks to measure model performance, robustness, safety, and bias.
  • Optimize production deployments through GPU efficiency, memory usage, latency reduction, and scaling strategies.
  • Collaborate with application engineering teams to integrate ML systems into backend, mobile, and desktop applications.
  • Monitor production ML systems and iterate quickly based on real-world performance and constraints.

Requirements

  • Strong background in deep learning and transformer-based architectures.
  • Hands-on experience training, fine-tuning, or deploying large-scale machine learning models in production.
  • Proficiency with machine learning frameworks such as PyTorch or JAX.
  • Experience with distributed training and inference frameworks such as DeepSpeed, FSDP, Megatron, ZeRO, or Ray.
  • Strong software engineering skills and experience building robust, maintainable, production-grade systems.
  • Experience optimizing GPU workloads, including memory efficiency, quantization, and mixed precision.
  • Ability to independently own end-to-end machine learning systems in fast-moving environments.
  • Strong problem-solving skills with a focus on rapid iteration and continuous improvement.
  • Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer (preferred).
  • Open-source contributions to machine learning or systems libraries (preferred).
  • Scientific computing, compiler technologies, or GPU kernel development (preferred).
  • Experience with RLHF pipelines, including PPO, DPO, or ORPO (preferred).
  • Experience training or deploying multimodal or diffusion models (preferred).
  • Experience with large-scale data processing frameworks such as Apache Arrow, Spark, or Ray (preferred).

Interested in this position?

Apply directly on the company website

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