Machine Learning Engineer Job at Robert Half, El Segundo, CA

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  • Robert Half
  • El Segundo, CA

Job Description

Job Description

Job Description

Machine Learning Engineer (Mid-Senior Level)

  • Compensation : $150K-$175K salary.
  • Work Environment : Hybrid flexibility in a West LA location (2-3 days onsite).

We are looking for a skilled Machine Learning Engineer to join our team in El Segundo, California. In this role, you will design, develop, and deploy cutting-edge machine learning models and artificial intelligence solutions. You will work closely with cross-functional teams to identify opportunities for AI integration and ensure the delivery of impactful, scalable solutions.

Responsibilities:

• Design and implement advanced machine learning solutions to address business challenges and drive innovation.

• Develop, train, and fine-tune machine learning models using tools such as TensorFlow, PyTorch, and Scikit-learn.

• Collaborate with cross-functional teams to identify opportunities for integrating AI into business processes.

• Research and apply the latest advancements in AI and machine learning to enhance existing systems and create new solutions.

• Deploy and monitor machine learning models in production environments, ensuring optimal performance and scalability.

• Conduct data exploration, preprocessing, and feature engineering on large-scale datasets to improve model accuracy.

• Work with cloud platforms such as Google Cloud Platform and AWS for scalable AI/ML implementation.

• Provide mentorship and guidance to less experienced team members, fostering a culture of knowledge sharing and collaboration.

• Ensure high-quality coding standards and participate actively in code reviews.

• Stay updated on industry trends and best practices to maintain the organization's competitive edge in AI.

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• At least 3 years of experience in software development or engineering with a focus on machine learning.
• Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding of machine learning algorithms, including Boosting Trees, Random Forests, and applied statistics.
• Hands-on experience with cloud platforms like Google Cloud Platform, AWS, or Databricks.
• Expertise in designing and deploying custom AI/ML solutions for real-world applications.
• Familiarity with Docker, Kubernetes, and distributed computing for scalable deployments.
• Excellent problem-solving skills and the ability to communicate complex technical concepts effectively to stakeholders.

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