Sr Machine Learning Engineer - Washington, DC

Overview

On Site
BASED ON EXPERIENCE
Full Time
Contract - W2
Contract - Independent

Skills

Machine Learning (ML)
Security clearance
Collaboration
Data collection
Data quality
Data cleansing
Data acquisition
Deep learning
scikit-learn
SANS
Algorithms
Data
Software deployment
Metrics
Management
Computer hardware
Probability
Distribution
Training
TensorFlow
Keras
Python
Pandas
OpenCV
Linux

Job Details

Job Title: Sr Machine Learning Engineer
Location: Washington, DC
Job Type: Full time/ Contract

Security Clearance: Needed

Job Description:
A Senior Machine Learning Engineer develops sophisticated algorithms and models that enable machines to learn from and make predictions on data. They work across the Client lifecycle, from data collection to model deployment, ensuring the solutions are efficient, scalable, and integrated into products effectively.

Responsibilities

  • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
  • Managing available resources such as hardware, data, and personnel so that deadlines are met
  • Analyzing the Client algorithms that could be used to solve a given problem and ranking them by their success probability
  • 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
  • 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
  • Defining validation strategies
  • Defining the preprocessing or feature engineering to be done on a given dataset
  • Defining data augmentation pipelines
  • Training models and tuning their hyperparameters
  • Analyzing the errors of the model and designing strategies to overcome them
  • Deploying models to production

Skills
  • Proficiency with a deep learning framework such as TensorFlow or Keras
  • Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
  • Expertise in visualizing and manipulating big datasets
  • Proficiency with OpenCV
  • Familiarity with Linux
  • Ability to select hardware to run an Client model with the required latency