Machine Learning Solutions Engineer
1 month ago
About the Role :
We are seeking a talented and creative Machine Learning Solutions Engineer to join our growing team. In this role, you will play a critical role in bridging the gap between business needs and cutting-edge machine learning solutions within the automotive industry. You will collaborate closely with application and product teams to define, develop, and implement ML solutions that solve real-world business :
- Partner with application and product teams to understand business challenges and opportunities.
- Translate business requirements into technical specifications for machine learning solutions.
- Design, develop, and implement machine learning models tailored to solve specific automotive industry problems.
- Define appropriate evaluation metrics for both offline model training and online model performance monitoring.
- Continuously monitor and improve model accuracy and performance through data analysis and feature engineering.
- Integrate diverse data sources into machine learning pipelines to enhance model effectiveness.
- Develop creative methodologies and approaches to optimize model performance.
- Design and build production-ready ML systems that integrate with existing applications and support real-time decision making.
- Communicate effectively with both technical and non-technical stakeholders, explaining complex ML concepts and business impacts.
- Stay up-to-date on the latest advancements in machine learning research and best practices.
Requirements :
- Master's degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
- Minimum 3-5 years of experience in applying machine learning techniques to solve real-world problems.
- Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning).
- Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages (Python).
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Solid understanding of statistical concepts and data analysis methods.
- Experience building and deploying production-ready machine learning systems (a plus).
- Experience working within the automotive industry (a plus).
- Excellent communication and collaboration skills to effectively interact with both technical and non-technical stakeholders.
- Strong problem-solving and analytical skills with a data-driven approach to decision making.
- Ability to work independently and manage multiple projects simultaneously.
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