Machine Learning Researcher

Kronos Research; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A financial technology firm based in Singapore is seeking an experienced Machine Learning Researcher to join their research team. This position involves designing and deploying deep learning models within high-performance trading systems. Candidates must have a strong background in machine learning and be skilled in programming languages like Python and C++. Prior experience with low-latency environments is advantageous.

Qualifications

• Strong mathematical and statistical background (probability theory, linear algebra, calculus).
• Experience with real-time, low-latency trading systems is a plus.
• Ability to develop scalable, robust machine learning models.

Responsibilities

• Understand and preprocess orderbook data.
• Design models for time-series and orderbook data.
• Implement parallelized data loading pipelines.
• Develop and optimize orderbook features using C++.
• Deploy models into real-time systems.

Skills

Proficiency in Python

Expertise in C++

Knowledge of Jax/PyTorch

Understanding of deep learning techniques

Experience in data analysis

Education

Degree in a relevant field (e.g., Computer Science, Mathematics)

Job description

We are seeking an experiencedMachine Learning Researcherto join our research team. This role requires expertise in designing and deploying deep learning models within high-performance, low-latency trading systems. You will be working on developing robust, scalable models and integrating them into our trading infrastructure.

Responsibilities

• Data Analysis & Preprocessing:Understand and preprocess orderbook data.
• Deep Learning Model Design:Design models for time-series and orderbook data (Transformers, RNNs, CNNs, Attention).
• Scalable Training Implementation:Implement parallelized data loading pipelines.
• Feature Engineering:Develop and optimize orderbook features using C++.
• Production Integration:Deploy models into real-time, low-latency systems.

Requirements

• Background in machine learning or quantitative research, preferably related to financial markets.
• Experience deploying ML models in real-time, low latency environments is a plus.
• Familiarity with optimizing model latency and inference speed(e.g., KV caching, quantization, pruning) is advantageous.
• Open to both experience candidates and highly motivated fresh graduated.

Technical Skills

• Programming Languages:Python, C++, Jax/PyTorch
• Model Optimization:Optimizing models for high-performance trading systems.

Analytical & Communication Skills

• Strong mathematical and statistical background (probability theory, linear algebra, calculus).
• Ability to articulate complex technical concepts.
• Passion for applying machine learning to quantitative finance.
• Drive to continuously improve models.

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