MLOPs Software Engineer

3 weeks ago

Singapore TECHNOLOGY SERVICES GROUP PTE. LTD. Full time
Roles & Responsibilities

Our company is at the forefront of innovation in financial technology. Our mission is to develop an AI-driven platform that predicts market trends, empowering retail investors with the tools previously only accessible to professionals. We're looking for a talented MLOPs Software Engineer with an interest in finance to join our growing team in our Singapore office.


Responsibilities

  • Focuses on MLOps from model training, model evaluation to trading evaluation. Portfolio to be requested here.
  • Develop large-scale deployment of GPU nodes running in dozens of Kubernetes clusters across regions. Core technologies may include: CUDA, Python, PyTorch, Triton, Redis, NCCL, NVLink.
  • Develop simulation pipelines to scale the testing of hyperparameters for model training and for trading. The innovation here lies in ability to synchronize model parameters with financial trading parameters.
  • Automate feature evaluation and experimentation for model training.
  • Automate model training and model performance evaluation.
  • Combine classical model evaluation with financial trading evaluation metrics such as Sharpe, Turnover, Fitness, Returns, Drawdown, Margin, Long Count, Short Count, Sector/Subindustry Allocations etc.
  • Build, maintain, enhance model pipelines using MLOps and AIOps frameworks.
  • Work with full suite of data and model infrastructure and integration i.e. SageMaker Studio or Vertex A.I.
  • Work with Data Scientists to setup model monitoring and feedback systems.
  • Part of a sub-team focusing on full autonomous AI Trading under a larger trading division.

Requirements:

  • Bachelor’s and above. Software Engineering background would be preferred.
  • Must have stack: CUDA, PyTorch, low level languages such as C++ or Go.
  • Must have experiences (Any of these passes):
    • High scale distributed training and inference systems and ML systems.
    • Parallel and distributed computing with multiple gpus at once
    • High throughput scheduling as a service particularly at supercomputing scale.
    • Understand how to resolve Segmentation Faults
  • Must have testing, debugging experiences: Unit Tests, Integration Tests, Errors Handling to ensure trading system remains fault tolerance and robust
  • Must have orchestration tools: DAGs in Airflow or Prefect, MLFlow
  • Must have deployment experiences: Docker, AWS, Load Testing etc
  • Good to have network technologies inside and out

Tell employers what skills you have

Classical
Airflow
Kubernetes
Pipelines
SageMaker
Software Engineering
Throughput
Trading System
PyTorch
CUDA
Python
Vertex
Docker
Debugging
Scheduling
C++

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