Senior Machine Learning Engineer - Full Remote

• Conduct quantitative research, focusing on, but not limited to, applying advanced statistical learning methods to diverse data sets in order to build robust models for forecasting stock risk and returns;
  
• Build efficient tools and scalable systems for the team;
  
• Idea generation, back-end testing, and implementation;
  
• Evaluate new datasets for potential inclusion in our Machine Learning models;
  
• Design and deliver Machine Learning Models and services supporting Learning Experience Platform and its components;
  
• Build the core and support systems for learning platform and develop features;
  
• Maintenance of the core and support systems by constantly updating the source codes and allied repositories;
  
• Develop technical documentation and maintain active tech repositories for all tech activities carried out;
  

• Master degree;
  
• 5+ years’ experience with programming languages such as C/C++, Java, Perl or Python and open-source technologies (Apache, Hadoop);
  
• Excellent skills in machine learning engineering with Python: PyTorch, TensorFlow, Caffe, Pandas, SciPy, OpenCV, Scikit-Learn;
  
• Experience in: Predictive modeling, Recommendation systems, Translation engine, Conversational AI;
  
• Academic and/or industry experience with standard AI and ML techniques, NLU, and scientific thinking;
  
• Experience working effectively with science, data processing, and software engineering teams;
  
• 5+ years’ experience with OO design and common design pattern;
  
• 5+ years’ experience with data structures, algorithm design, problem-solving, and complexity analysis;
  
• 3+ years’ experience developing cloud software services and an understanding of design for scalability, performance, and reliability;
  
• Experience defining system architectures and exploring technical feasibility trade-offs;
  
• Experience optimizing for short term execution while planning for long term technical capabilities;
  
• Academic and/or industry experience with standard AI and ML techniques, NLU, and scientific thinking;
  
• Experience working effectively with science, data processing, and software engineering teams;
  
• Database: RDBMS DB like MariaDB / MySQL, Postgres, SQL and NoSQL DB like Elastic Search, MongoDB, Cassandra etc;
  
• Container Technologies: Kubernetes, Docker;
  
• System Admin: BASH, Git;
  
• Fluent in English;
  

• Preferred engineering experiences: MLOps, MATLAB, and Java, Cloud platform experience: Azure and AWS;
  
• Ability to prototype and evaluate applications and interaction methodologies;
  
• Ability to produce code that is fault-tolerant, efficient, and maintainable;
  

Originally posted on Himalayas