Position: Full-Stack Software Engineer - Machine Learning
Company: Grid Dynamics
Category: DevOps
Experience required: 3y
English level: intermediate

Do you want to impact the future of ML for Manufacturing here at project by developing an extraordinary platform?
The goal of our team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. We’re looking for experienced machine learning professionals to help us revolutionize how we manufacture project’s amazing products. Put your experience to work in this highly visible role.

Key Responsibilities:
- Build self-serve web-based applications using Python and JS.
- Build pipelines and internal tools (MLOps) to accelerate ML modeldevelopment and production in cloud-based environment (AWS).
- Develop and productionalize ML algorithms and systems (regression,classification, and deep learning).
- Develop optimization models for black-box optimization applications.
- Analyze large amounts of data to identify anomalies (patterndetection) and identify predictive signals.
- Develop machine analytics and IoT solutions for manufacturing.

Key Qualifications:
- 5+ years of experience building frontend/backend web applications.
- 3+ years experience in productionalizing ML system (MLOps).
- 3+ years experience in cloud-based ML dev and deployment (AWS)
- Strong programing skills with proficiency in Python and Github.
- Experienced user of machine learning libraries such as scikit-learn, scipy, and Tensorflow/PyTorch.

Bonus Points:
- Knowledge of full-stack ML development such as Flask (backend), Bokeh, Holoviews or Dash (front-end).
- Experience with Operations Research (OR) and nonlinear constrained or black-box optimization.
- Experience in machine data (sensors, downtime, machine states, etc) for IoT & predictive maintenance applications.
- Experience applying deep learning frameworks, such as PyTorch/ Torch, TensorFlow, Keras to real world applications.
- Experience in data analytics, machine learning and/or computer vision for manufacturing problems is a bonus.