Machine Learning Specialist (Deep/Reinforcement Learning)

ioTech Solutions; Singapore; On-site; USD 80,000 - 150,000; Full time

Job summary

An innovative firm is seeking a skilled machine learning specialist to join their dynamic team. In this role, you will design and implement cutting-edge machine learning algorithms and deep learning applications that tackle complex business challenges. Collaborating closely with data scientists, traders, and developers, you will optimize models for trading systems and construct efficient data pipelines. This position offers a unique opportunity to work at the forefront of technology in the financial sector, where your contributions will directly impact trading strategies and performance. If you are passionate about machine learning and eager to make a difference, this role is perfect for you.

Qualifications

• Master's or Ph.D. in a quantitative field is required.
• Experience in financial industry is a bonus.

Responsibilities

• Design and implement machine learning algorithms to solve complex problems.
• Collaborate with teams to optimize models for trading systems.

Skills

Machine Learning

Deep Learning

Python

R

Julia

Statistical Analysis

Education

Master's degree in Computer Science

Ph.D. in Statistics

Degree in Mathematics

Degree in Automation

Tools

TensorFlow

PyTorch

Job description

Job Description:

My client is a multi-strategies leading quantitative trading company, they are hiring a machine learning specialist (in reinforcement or deep learning) to empower their team.

Your key responsibilities will include:

1. Designing and implementing machine learning algorithms and deep learning applications to solve complex business problems.
2. Collaborating with data scientists, traders, researchers, and developers to optimize machine learning models into trading systems and strategies.
3. Constructing optimized data pipelines to feed machine learning models and trading performance monitoring.
4. Conducting research on the latest advancements in machine learning and exploring innovative techniques to enhance our systems.

Qualifications:

1. Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Automation, or a related quantitative field.
2. Prior experience in the financial industry is a bonus but not a must.
3. Proficiency in programming languages such as Python, R, or Julia, and familiarity with machine learning libraries like TensorFlow, PyTorch, or other machine learning frameworks.
4. Experience in computationally intensive research on very large data sets.