Requirements

• 4+ years of shown hands-on experience with design, implementation, and application of ML/AI/Deep Learning and OR solutions and techniques to build models that solve real problems.
• 2+ years of hands-on experience in optimization modeling, simulation, and analysis with Python or Matlab.
• Experience analyzing machine data (sensors, downtime log, machine states, etc) for IoT & predictive maintenance applications.
• Experience applying deep learning frameworks, such as PyTorch/ Torch, TensorFlow, Keras to real-world applications that solve problems.
• Knowledge of validated approaches for scale-ability, productionalizing models, and implementing machine learning applied to expansive and diverse datasets (storage GPUs, techniques for deep learning at scale).
• Strong software development skills with proficiency in Python.
• Experienced user of machine learning and statistical-analysis libraries, such as GraphLab Create, scikit-learn, scipy, and NLTK.
• High level of autonomy and influence to remove roadblocks and deliver results (evaluate and solve complex problems involving various teams ranging from data instrumentation to analytics tool development). A proven track record for self-study and self-exploration into new tools and techniques.
• Ability to explain and present analyses of machine learning concepts to a broad technical audience.
• Experience with image processing, Computer Vision, and using ML tools to identify patterns in images, specifically applied to industrial or manufacturing environments is a plus.
• Applied background in Hadoop, Spark, Hive, Cassandra, and knowledge of R is a plus.
• Experience in data analytics for manufacturing problems is a plus.
• Master’s or Ph.D. degree in Computer Science, Math, Statistics, Physics, Engineering, or related level of experience required.

Responsibilities

• Collaborate with robotics and automation specialists, mechanical and quality engineers to apply machine learning to industrial problems and situations
• Seek opportunities in the production and development processes to utilize deep learning, algorithms, and other machine learning tools for improvements
• Implementation of machine learning (ML) and operations research (OR) tools, such as classical regression, classification, as well as neural networks and various optimization models for a wide range of prescriptive/predictive applications in dynamic production environments
• Develop a toolkit to guide the application of machine learning tools combined with statistical tools for common engineers
• Assemble large data sets for analysis either through direct SQL-based querying or development of scripts and code-modules to collate distributed and disparate data sources
• Analyze huge amounts of data-identifying anomalies (pattern detection) and variabilities in a measure of interest
• Develops software components in Python, R, and/or C/C++/ Objective-C towards the roll-out of a data automation system Qualifications

What we offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Flexible schedule
• Medical insurance
• Benefits program
• Corporate social events
• Professional development opportunities