Machine Learning Engineer, Integrations

**About the job**:
At Datature, we are building a platform for training and deploying machine learning models swiftly without a single line of code. Datature Nexus is an MLOps platform that allows users to label unstructured data and construct complex machine learning pipelines all in their browsers using highly visual editors.

Our users have leveraged our platform to solve problems in a myriad of verticals - from grading crops to optimizing manufacturing to identifying diseases from MRI scans. Datature levels the playing field for teams and companies in most industries to start AI-driven revolutions of their own.

**The Scope**

As part of the integration team, you will be working directly with Datature Users to integrate our MLOps Platform directly into their stack, and ideate ways to optimize their computer vision implementation.

You will be expanding our neural network offerings, cutting-edge features, and model observability functions for our users. In addition, you will be working on Datature’s Insights and MLOps offering to help users build better, fairer, models.

In addition, you will scout and prototype with state-of-the-art vision algorithms and methods to provide our users and the team with potentially disruptive technologies that can be integrated into the Datature platform to improve user value.

Ideally, you enjoy research, prototyping, and sharing new ideas based on real-user feedback and problems to work on a roadmap of ambitious features that we ship to our users in our quarterly platform updates.

**Requirements**:

- 2-5 years of experience researching, implementing, and deploying computer vision / deep-learning algorithms
- Contribute to research, design, and implementation of state-of-the-art perception / vision algorithms, taking ideas from paper to integration with users and clients
- Experience with stacks that include **PyTorch, JAX, Keras, TensorFlow, OpenCV, FFMPEG**:

- Possess some technical foundation in working with backend services, querying large amounts of data, and leveraging Google Cloud Platform / Cloud GPU Resources
- Collaborate with key stakeholders and client teams to understand business requirements and objectives related to ML integration
- Experience building, maintaining, and debugging real-time computer vision systems
- Experience and passion in Deep-Learning Algorithms, serving APIs leveraging CUDA, Multi-GPUs, and ML Development workflows
- Experience with computer vision research, prototypical notebooks for testing ideas, and implementing the latest research ideas swiftly

**About You**

You are a machine learning enthusiast who follows state-of-the-art computer vision publications and repositories. Ideally, you have the ability to write clean, but powerful, prototypical Jupyter Notebooks for our users to understand various computer vision methods.

Above all, you have a passion for data, machine learning, and user experience. You understand the tradeoffs with each line of code and have an idea of what the various priorities are with each project.

Ideally, you have a portfolio of Kaggle notebooks, discussions, or a technical blog that shows your ideas and interests in writing.

**Why You'll Love Us**

We are a technology-first team dedicated to developing the most intuitive and performant platform to shape the way users think about building machine learning capabilities. We are a quirky group of engineers whom you will enjoy debating about codes and algorithms with.

You will be solving the most important problems at the intersection of machine learning, data processing, and client engineering. You will have the largest impact on the model architectures and optimization offerings that users have access to.

If this is your cup of tea, we would love to hear from you.

**Do include links to previous projects, GitHub profiles, Kaggle profiles, or any links that might help us learn more about you