At HyperScience we bring AI to the enterprise. Our products help enterprises become more productive, efficient, and competitive by automating various types of office work and reducing bureaucratic burden both on businesses and their customers. We take a heterogeneous approach to AI, using a blend of what are traditionally considered different fields of ML: deep learning, computer vision, and NLP among others. We believe that delivering AI to the enterprise is the key to unlocking new applications of human potential, and we are excited to execute on our plan to do so. ML is at the core of what we do. We productize ML lab experiments into enterprise-ready AI solutions - and we’re looking for continuous learners to lead these efforts. This is an opportunity to both research cutting edge ML techniques and to implement them at a fast-growth AI startup.
As a Machine Learning Engineer You Will:
- Actively follow advancements in AI and create ML models.
- Improve existing ML models: everything from tweaking the dataset to replacing the approach with a demanding end-to-end (deep learning) solution.
- Assess the risks and merits of different approaches to solving a problem in the light of the specific requirements and time frames.
- Actively work on creating and improving tools to parallelize training of the models, unifying dataset creation and accuracy measurements across experiments.
- Closely monitor the edge cases of the models performance and taking active measures of explaining the reasons and possible approaches for diminishing their effects.
- Be actively involved in the process of productizing a lab experiment into an enterprise-ready AI solution.
What You'll Achieve:
- Within your first 60 days:
- You will become familiar with TensorFlow and our custom ML framework.
- You will get acquainted and eventually be fully comfortable navigating the ML codebase, the technology stack, the development processes and org structure within the company
- You will have made significant contributions to at least one of our models and/or training framework.
- You will see your research efforts being implemented in production grade software
- After 60 days and beyond:
- You will be an integral part of the team, designing your own experiments, dataset generation, and feature development.
- You will take ownership of one or more models, maintaining and improving their performance in testing and production environments.
- You will be taking an active role in finding possible problems and solutions, different approaches, and new explorations.
Desired Experience:
- BA/BS (MS or PhD preferred) in a relevant field (CS, engineering, etc) or equivalent hands-on experience.
- Background in Deep Learning, Natural Language Processing (NLP), or Computer Vision
- Proficiency in Tensorflow and/or other deep-learning frameworks strongly encouraged
- Good understanding of linear algebra, analysis, probability and statistics fundamentals
- Experience with one or more general purpose languages (Java, C/C++, Python, etc)
- Desire to carve out your own role in a fast-moving, agile environment
- Team player with strong communication skills
by via developer jobs - Stack Overflow
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