Software Engineer - Machine Learning

Quantiply Corporation

$120K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in computer science, machine learning, electrical engineering, mathematics, or equivalent experience.
  • Proficiency in Python, Docker, and Kubernetes.
  • Hands-on experience with TensorFlow.
  • Familiarity with distributed software architecture.
  • Understanding of machine learning and statistics.

Responsibilities

  • Develop scalable deep learning, reinforcement learning, and Bayesian models.
  • Create innovative designs for end-to-end machine learning systems.
  • Optimize performance of machine learning systems in parallel environments.
  • Design and develop software libraries.
  • Collaborate with Product and Engineering teams to identify new opportunities.
  • Influence product features and roadmap with exploratory analysis.
  • Communicate software developments through reports and presentations.

Benefits

  • Work alongside top researchers in the field.
  • Contribute to impactful projects in Anti-Money Laundering.
  • Opportunity to innovate in machine learning techniques.
  • Collaborative and demanding team-oriented environment.
  • Chance to influence product direction and development.
Full Job Description
Job Description

We're looking for software engineers with experience in machine learning and artificial intelligence. You will be embedded as part of a team that collaborates with researchers on conceiving, researching, and prototyping new machine learning techniques and use cases with the goal of driving Quantiply's growth in the Anti-Money Laundering space.

Ideal candidates will have a good understanding of state-of-the-art techniques in machine learning and deep learning, performance optimization, and benchmarking, along with a strong understanding of high-performance computer architecture. Candidates must also possess strong verbal and written communication skills and the demonstrated ability to work in a demanding team-oriented environment.

Responsibilities:
  • Develop highly scalable deep learning, reinforcement learning and bayesian models.
  • Support research projects by providing innovative designs for end-to-end Machine Learning systems.
  • Optimize performance of complex machine learning systems. Exploit modern parallel environments.
  • Design and develop software libraries.
  • Partner with Product and Engineering teams to explore new opportunities.
  • Influence product features and product roadmap through exploratory analysis.
  • Report and present software developments verbally and in writing.


Qualifications

Minimum qualifications:
  • PhD in computer science, machine learning, electrical engineering, mathematics, or equivalent pracitical experience.
  • Strong knowledge and experience in Python, Docker and Kubernetes.
  • Working experience in Tensorflow.
  • Working experience with distributed software architecture.
  • Knowledge of machine learning and statistics.

Preferred qualifications:
  • Strong experience in Tensorflow or similar frameworks.
  • Strong experience with concurrent and distributed software architecture.
  • Experience with Hadoop.
  • Experience with C++/Java/Scala.


Additional Information

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