As a Data Engineer / Solutions Architect at Holo you will be part of the cross-functional team of technology and business teams to build the next generation of additive manufacturing tools. You will be working with terabytes of text, images, and other types of data to solve real-world problems. Designing and running experiments, researching new algorithms and finding new ways of optimizing the manufacturing process.
We are searching for top Machine Learning Data Engineers / Solutions Architects capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
- Use deep learning, machine learning and analytical techniques to create scalable solutions for business problems
- Design, development and evaluation of highly innovative models for predictive learning, content ranking, and anomaly detection
- Interact with customer directly to understand the business problem, help and aid them in implementation of DL/ML algorithms to solve problems
- Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
- Work closely with product and engineering team to drive model implementations and new algorithms
- BS and Masters degrees in computer science, or related technical, math, or scientific field
- 6+ years of professional experience in a business environment
- 4+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
- 2+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
- PhD degree in computer science, or related technical, math, or scientific field
- Strong working knowledge of deep learning, machine learning and statistics.
- Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Caffe, Torch, Theano or similar.
- Experience in using Python, R or Matlab or other statistical/machine learning software
- Strong communication and data presentation skills
- The motivation to achieve results in a fast-paced environment.
- Experience with statistical modelling / machine learning
- Strong attention to detail
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Ability to think creatively and solve problems