Demo

Machine Learning Engineer

Quanta Search
New York, NY Full Time
POSTED ON 1/10/2025
AVAILABLE BEFORE 3/10/2025
Our client is a process driven investment management group consisting of a team of researchers, traders and technologists who harness and apply the power of technology and automation to identify, model and trade global financial markets.  This division offers an array of quantitative investment fund products to its clients.
They are seeking candidates with exceptional academic credentials to join their team and participate in and support of the firm’s efforts in the research, trading and production processes.
They look for candidates who are eager to make an impact by doing real, hands-on research and development.  Candidates must possess exceptional knowledge of mathematical and statistical methods as well as a proven ability to solve complex problems.  A desire to work with large data sets and apply creative thinking is required. Successful candidates will also have deep interest in learning about trading and the financial markets. 
They offer a supportive environment that fosters independent thought in a collegial, results oriented, work setting.  Researchers and developers there are passionate about their work, model building, data and technology.  
You are curious and intellectually driven to succeed.  You'll be provided with the tools, resources and training required to satisfy that curiosity and passion, leading them to new insights and discoveries.  Their process driven approach enables these insights to be thoroughly tested in a systematic fashion and ultimately, if confirmed, integrated into the portfolio.
Role: 
Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud computing. Machine Learning Engineers should be comfortable with data engineering and should have an interest in the data science.
What they will do:
They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Minimum Requirements:
  • Strong understanding of statistical analysis and computational modelling.
  • Strong understanding of algorithms and data structures.
  • Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
  • TensorFlow (or another GPU integrated deep learning library).
  • Deep understanding of machine learning algorithms.
  • Deep understanding of numerical optimization.
  • Strong understanding of data structures and algorithms.
Plus, but not required:
  • Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
  • Experience building industrial grade ETL pipelines.
  • Experience building frontend systems.
  • Familiarity with dashboards and other visualization tools.
  • Ability to derive generalization bounds for common ML algorithms.
  • Experience developing new machine learning algorithms.

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