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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