Full-Time

Machine Learning Engineer

Updated on 9/4/2026

Adidev Technologies

Adidev Technologies

No salary listed

No H1B Sponsorship

Chicago, IL, USA

Remote

Category
AI & Machine Learning (1)
Required Skills
LLM
MLOps
Microsoft Azure
Python
TensorFlow
Neural Networks
PyTorch
Machine Learning
OpenAI
Data Engineering
AWS
Data Modeling
Databricks
Data Analysis
Google Cloud Platform
Requirements
  • Experience architecting and developing artificial intelligence or machine learning solutions on platforms such as AWS, Databricks, Azure, Google Cloud, and OpenAI.
  • A software engineering and/or data engineering background, especially in one of the major cloud platforms.
  • Hands-on experience with deep learning, large language models, Python, TensorFlow, PyTorch, and other artificial intelligence frameworks.
  • Experience putting machine learning and artificial intelligence systems into production, including knowledge of relevant best practices and pitfalls.
Responsibilities
  • Architect and refine sophisticated machine-learning models and algorithms, translating complex datasets into actionable solutions.
  • Engage in the full lifecycle of data-modeling projects, from understanding business requirements through deployment and monitoring.
  • Execute comprehensive data analysis, including data preprocessing, feature engineering, and use of generative artificial-intelligence algorithms for novel solutions.
  • Lead cross-functional collaborations to integrate generative artificial-intelligence models into offerings, enhancing product capabilities and user experiences.
  • Apply advanced analytical techniques to analyze large datasets and identify trends, anomalies, and opportunities for improvement.
  • Execute data preprocessing, feature engineering, and algorithm optimization to improve model accuracy and efficiency.
  • Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.
  • Keep current with and implement the latest machine-learning trends, tools, and best practices, including automated machine learning, machine-learning operations, and interpretability frameworks.
  • Promote compliance with industry standards and regulatory requirements, emphasizing ethical artificial-intelligence practices.

Company Size

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Company Stage

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Total Funding

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Headquarters

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Founded

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