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Open nowFirst seen 13 hours ago

Machine Learning Engineer

Workaholic36012 open roles

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Your applicationOpen nowMachine Learning EngineerWorkaholic360

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 13 hours ago

The posting

Machine Learning Engineer

Job Brief:

We are seeking a talented Machine Learning Engineer to join our team and contribute to the development and deployment of cutting-edge machine learning models and algorithms. The ideal candidate will have a strong background in machine learning, deep learning, and software engineering, with a passion for solving complex problems and delivering impactful solutions.

Responsibilities:

  • Design, develop, and deploy machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to define project requirements, collect and preprocess data, and evaluate model performance.
  • Research and implement state-of-the-art machine learning techniques and algorithms to improve model accuracy and efficiency.
  • Develop and maintain scalable and reliable machine learning pipelines for training, evaluation, and inference.
  • Optimize machine learning models for performance, scalability, and resource efficiency.
  • Conduct experiments and A/B tests to evaluate model performance and validate hypotheses.
  • Collaborate with software engineers to integrate machine learning models into production systems and applications.
  • Stay up-to-date with the latest trends and advancements in machine learning and artificial intelligence.

Requirements:

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field. Masters or Ph.D. preferred.
  • 3+ years of experience in machine learning engineering or related field.
  • Strong proficiency in Python programming language and machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Solid understanding of machine learning concepts and algorithms, including supervised learning, unsupervised learning, and deep learning.
  • Experience with data preprocessing, feature engineering, and data visualization techniques.
  • Familiarity with software engineering best practices, version control systems, and agile methodologies.
  • Excellent problem-solving skills and ability to work independently or collaboratively in a team environment.
  • Strong communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Knowledge of distributed computing frameworks such as Apache Spark or Dask.
  • Familiarity with natural language processing (NLP) techniques and libraries.
  • Experience with reinforcement learning, computer vision, or time series analysis.
  • Contributions to open-source projects or participation in the machine learning community.
  • Certification in machine learning or artificial intelligence from recognized institutions.
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