Software Engineer - Machine Learning
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.
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.
All your information will be kept confidential according to EEO guidelines.