Senior Machine Learning Engineer
| Company | General Motors |
|---|---|
| Location | Austin, TX, USA, Warren, MI, USA |
| Salary | $130800 – $211200 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field or equivalent experience.
- 5+ years of experience in machine learning engineering, data science, or a related field.
- Experience with Azure cloud services, particularly Azure Machine Learning and Azure Databricks.
- Familiarity with MLflow for model management and experimentation.
- Strong proficiency in React for frontend development.
- Proficiency in Python for machine learning and data analysis.
- Knowledge of machine learning algorithms, statistical modeling, and data structures.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- Strong problem-solving mindset and a proactive attitude towards learning and self-improvement.
Responsibilities
- Provide technical expertise and support to POD teams in the development and implementation of machine learning and AI solutions, leveraging Azure, Databricks, and MLflow.
- Collaborate with product teams to design scalable and efficient solutions, ensuring alignment with architectural best practices and business requirements.
- Assist in the development and optimization of machine learning algorithms and models, providing guidance on best practices and methodologies.
- Support the design and implementation of data pipelines for data ingestion, processing, and feature engineering, ensuring data quality and integrity.
- Assist in the deployment of machine learning models into production environments, implementing monitoring and logging mechanisms for performance tracking.
- Collaborate with frontend developers to support the implementation of responsive and user-friendly web interfaces using React, integrating machine learning capabilities seamlessly into frontend applications.
- Work closely with product teams, data scientists, software engineers, and business stakeholders to understand requirements, provide technical guidance, and ensure successful project delivery.
- Document technical solutions, processes, and best practices, and share knowledge with team members to facilitate learning and collaboration.
Preferred Qualifications
- Experience with version control systems (e.g., Git) and containerization technologies (e.g., Docker) is desirable.