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Machine Learning Engineer Entry Level

Remote: 
Full Remote
Experience: 
Junior (1-2 years)
Work from: 

Offer summary

Qualifications:

Bachelor's degree in Computer Science or related field, At least 1 year of hands-on experience, Proficiency in Python and PyTorch, Familiarity with AWS SageMaker.

Key responsabilities:

  • Develop, train, and optimize machine learning models
  • Implement scalable machine learning workflows and deploy solutions
BigBear.ai logo
BigBear.ai SME https://bigbear.ai/
501 - 1000 Employees
See more BigBear.ai offers

Job description

Overview

BigBear.ai is seeking a AI/ML Engineer with at least 1 year of hands-on experience in developing machine learning models using Python, specifically with PyTorch, and deploying solutions on AWS SageMaker. As part of our dynamic team, you will collaborate with data scientists, engineers, and product teams to build and deploy scalable machine learning solutions that drive innovation and solve complex problems.

What You Will Do

  • Develop, train, and optimize machine learning models using PyTorch for various use cases such as computer vision, NLP, or predictive analytics
  • Implement scalable machine learning workflows and deploy models using AWS SageMaker
  • Collaborate with cross-functional teams to gather requirements, refine models, and ensure seamless integration with production systems
  • Write efficient, maintainable, and reusable code in Python for machine learning pipelines
  • Evaluate model performance, conduct error analysis, and implement improvements
  • Manage and preprocess large datasets to ensure data quality and suitability for machine learning applications
  • Leverage other AWS services (e.g., S3, Lambda, EC2) to support model deployment and monitoring
  • Stay updated on the latest developments in machine learning and actively contribute to process improvement and innovation within the team

What You Need To Have

  • Education: Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field
  • Experience: At least 1 year of hands-on experience developing machine learning models in Python, with a focus on PyTorch
  • Familiarity with AWS SageMaker, including model training, deployment, and monitoring
  • Solid understanding of fundamental machine learning concepts such as supervised/unsupervised learning, evaluation metrics, and feature engineering
  • Proficiency in handling and preprocessing datasets using tools such as Pandas, NumPy, and other data libraries
  • Experience with version control systems like Git
  • Strong analytical, problem-solving, and communication skills

What We'd Like You To Have

  • Familiarity with AWS services such as S3, Lambda, EC2, and CloudWatch
  • Basic knowledge of DevOps practices, including CI/CD pipelines for machine learning workflows
  • Exposure to additional deep learning frameworks such as TensorFlow
  • Knowledge of MLOps principles and tools for monitoring and managing deployed models
  • Experience working in Agile development environments

About BigBear.ai

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on BigBear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in Columbia, Maryland, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.

Required profile

Experience

Level of experience: Junior (1-2 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Communication
  • Analytical Skills
  • Problem Solving

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