Machine Learning Engineer Offline

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 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 roll-out of a data automation system Qualifications

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 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 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 PhD degree in Computer Science, Math, Statistics, Physics, Engineering or related level of experience required.

Company 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