Remote:::Machine Learning Engineer

Location: Portland, Oregon, United States
Type: Full-time
Posted: 03.SEP.2021
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HI, Kindly let me know if you have a suitable fit for the following position Thanks Title: Machine Learning Engineer Location: 100% REMO...



Kindly let me know if you have a suitable fit for the following position


Title: Machine Learning Engineer

Location: 100% REMOTE

Duration: 6 months

Only W2

Please send the resume to or 847-


  • Proficiency with a deep learning framework such as TensorFlow or Keras
  • Proficiency with languages such as JavaScript, HTML, Python, SQL, and C++.
  • Expertise in visualizing and manipulating big datasets (pulling from AWS, CRMs, etc)
  • Proficiency with OpenCV
  • Familiarity with Linux
  • Ability to select hardware to run an ML model with the required latency
  • Familiarity with ServiceNow and/or Microsoft Azure Bot Services preferred
  • Excellent interpersonal, communication and organizational skills are required. Excellent analytical and troubleshooting skills are necessary.
  • Strong written communication skills are preferred, as is the ability to adapt to and follow an organization's voice, tone, and style.
Breakdown of time:
  • Analysis- 50% of the time
  • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
  • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
  • Verifying data quality, and/or ensuring it via data cleaning
  • Supervising the data acquisition process if more data is needed
  • Finding available datasets online that could be used for training
  • Design - 25% of the time
  • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
  • Defining validation strategies
  • Defining the preprocessing or feature engineering to be done on a given dataset
  • Defining data augmentation pipelines
  • Deploy - 15% of the time
  • Managing available resources such as hardware, data, and personnel so that deadlines are met
  • Training models and tuning their hyperparameters
  • Analyzing the errors of the model and designing strategies to overcome them
  • Deploying models to production
  • Collaboration - 10% of the time
  • Collaborating with customers, stakeholders, and service owners to build out solutions
Charan Kumar | IVY Tech Sols Inc.

3403 N Kennecott Avenue, Suite B&C Arlington Heights, IL 60004

( Direct:
  • |Gtalk : charan.ivytech|
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