ParticleB is a data technology provider company based in Tehran. Experienced in AI and machine learning technologies, we are focused on financial markets and algorithmic trading.
We are looking for a machine learning engineer to help us build machine learning pipelines in production. Having a piece of profound knowledge of machine learning theory and a solid skillset in ML pipeline design, deployment, and maintenance, the appropriate candidate is responsible for the design and deployment of data and compute-intensive ML pipelines.
Responsibilities:
Research on currently developed AI models or state-of-the-arts and apply them to defined problems
Collaborate and coordinate with data scientists to design suitable ML pipelines in production
Propose and build evaluation frameworks, online training, and optimization procedures to maintain performance in production
Develop processes and tools to monitor, analyze and validate model performance
Maintain ML services in production
Qualifications:
Familiar with statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
Deep Knowledge and understanding of a variety of machine learning concepts and techniques (feature space, generalization, classification, clustering, loss functions, gradient descent, etc.) and their real-world advantages/drawbacks
Detailed knowledge of machine learning evaluation metrics and best practices
Familiar with trading concepts and portfolio evaluation metrics is a big plus.
Familiar with hyperparameter optimization techniques
Strong Python coding skills
Familiar with Docker and airflow is an advantage
Excellent written and verbal communication skills (English) for coordinating across teams, research and reporting
Linux SysAdmin skills are a strong plus.
Minimum work experience of 2 years is required.
Position Details:
full-time
Flexible hours
Highly competitive pay
Young and dynamic environment
Challenging problems and state of the art technologies
معرفی شرکت
ParticleB is aiming to apply scientific research in AI and data analytics to products using a problem design mindset. We are currently focused on developing an automated trading platform tailored specifically to optimize risk-anchored portfolios. Natural language processing, exploratory data analysis, recommendation systems and data storytelling are also a few domains in which we have ongoing projects