Overview

We are looking for an incredibly bright Senior Machine Learning Engineer to join our growing Platform Machine Learning engineering team.

If you have passion and hands-on experience solving real-world business challenges using machine learning in large scale systems, a strong track record building deep learning models and deploying them in production, and want to make a huge positive impact in people’s lives around the world, then this is a great opportunity for you.

The role involves application of machine learning and other related techniques in areas of natural language processing, predictions and recommendations to improve user experiences and decision making, customer service, security, image recognition and retrieval, and more. If you are the kind of person who thrives in a challenging environment and has creative expertise and a thirst for pushing the limits, we are interested in you!

Our platform teams are comprised of talented Software Engineers who get a thrill out of solving hard problems, working in a full stack environment, delivering quality code at scale, and enhancing performance and functionality. If this is you, let us know and you can be a part of it.

Responsibilities
Work with our engineering and product teams, translating their requirements and applying the latest machine learning techniques to solve real business problems, improve our platform, and develop new capabilities
Participate in interviews and help build a world-class team of engineers
Design, build, and train custom models and evaluate model performance
Help the team deploy production ready models to customers, to learn from customer feedback and make frequent model improvements
Contribute to the overall architecture and implementation of our ML infrastructure, data pipelines, inference engine(s), APIs, and products
Collaborate with our engineering and product teams to understand their machine learning related needs and to provide guidance and support where necessary
Provide mentoring and technical direction for more junior team members where needed
Follow best practices and share them with the team
Participate in functional, technical, and code reviews
Work in an Agile environment

Company:

Q Systems International Inc.

Qualifications:

Minimum Qualifications
3+ years of hands-on experience working with neural networks and other statistical techniques and successfully delivering and running such systems in production
A Masters or Ph.D in Computer Science or related field, concentration in Machine Learning is preferred
Hands-on experience with ML infrastructure development and support using cloud computing technologies
Fluent in using a neural network framework such as TensorFlow, Caffe, PyTorch, or Theano with understanding of back-propagation and other mathematical concepts employed by modern ML methods
Fluent in Python, including experience with packages such as NumPy and pandas
Proficient with SQL, notably writing and optimizing queries
Preferred Qualifications
Experience in data engineering and architecture
Experience in applying machine learning for a global-scale enterprise or consumer application
Demonstrated knowledge and ability working with AWS, Google Cloud, or other cloud-based solutions to train models, set up data pipelines, and set up inference engines
Experience in microservices, Kubernetes, Docker, or other containerizers
Working knowledge of Node.js, JavaScript, and related technologies and frameworks
Experience with developing ML methods in Jupyter Notebooks environment
Experience with developing NLP models, e.g. for chatbots or automated assistants
Knowledge of Continuous Integration & Delivery methodologies
Excellent problem-solving skills especially debugging of complex software systems
Excellent written and verbal communication skills
A passion for applying latest technologies into the development of innovative features and products
A collaborative attitude and demonstrated team-working ability
Self-motivated with a strong passion for learning

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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