Devron's engineering team is involved in developing the next generation privacy-preserving machine learning systems. We need engineers who can bring in new ideas, and build prototypes, and deploy new products in a short time-scale. As a machine learning engineer, you will be involved in multiple projects that are critical to Devron's needs and be interested in leading teams as we grow.
Our team just came out of the intelligence community, a few from the CIA - to productize an approach with lessons learned from one of the most sensitive environments to build machine learning applications in.
We're based out of NYC and DC - backed by Fintech Collective, Afore Capital, Evan Weaver (CTO of FaunaDB), Tim Chen @ Essence VC and more.
- Expertise in Machine Learning, Computer Vision, and scalable statistical techniques (e.g. unsupervised machine learning, logistic regressions, random forest, SVMs).
- Expertise in utilizing scalable data insight platforms and tools. Representative examples would include: programming skills (e.g. Python, TensorFlow, PyTorch), cloud platforms such as (GCP, AWS, etc).
- Exposure to machine-learning model lifecycle; training, evaluation, serving.
- Interest in deploying machine-learning models as scalable services.
- Interest in "tool-making"; building features for developers that empower them and make them faster.
- Curious about attacker incentives and how malicious behavior can be identified in data.
- A strong communicator with the ability to build meaningful customer relationships.
- A strong contributor is highly cross-functional efforts who is not afraid to step in and lead a technical project.
- Enthusiastic about innovating in fast-growing privacy and artificial intelligence space.
- Have a natural inclination to work in a fast-paced startup culture ready to take up multiple responsibilities.