Machine Learning Engineer
4 weeks ago
About the Role :
We are seeking a highly skilled and experienced Machine Learning Engineer to join our dynamic team.
As a Machine Learning Engineer, you will be responsible for the design, development, deployment, and maintenance of machine learning models and systems that drive our [mention specific business area or product, e.g., recommendation engine, fraud detection system, autonomous vehicles].
You will work closely with data scientists, software engineers, and product managers to translate business needs into scalable and reliable machine learning solutions.
This is a key role in shaping the future of CBRE and requires a strong technical foundation combined with a passion for innovation and :
Model Development & Deployment :
- Design, develop, and deploy machine learning models using various algorithms (e.g., regression, classification, clustering, deep learning) to solve complex business problems.
- Select appropriate datasets and features for model training, ensuring data quality and integrity.
- Implement and optimize model training pipelines, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
- Deploy models to production environments using containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure).
- Monitor model performance in production, identify and troubleshoot issues, and implement model retraining and updates as needed.
Infrastructure & Engineering :
- Develop and maintain APIs for model serving and integration with other systems.
- Write clean, well-documented, and testable code.
- Collaborate with software engineers to integrate models into existing products and services.
Research & Innovation :
- Stay up to date with the latest advancements in machine learning and related technologies.
- Research and evaluate new algorithms, tools, and techniques to improve model performance and efficiency.
- Contribute to the development of new machine learning solutions and features.
- Proactively identify opportunities to leverage machine learning to solve business challenges.
Collaboration & Communication :
- Collaborate effectively with data scientists, software engineers, product managers, and other stakeholders.
- Communicate technical concepts and findings clearly and concisely to both technical and non-technical audiences.
- Participate in code reviews and contribute to the team's knowledge sharing.
- Version Control : Experience with Git and other version control systems.
- DevOps : Familiarity with DevOps practices and tools.
Strong understanding of machine learning concepts and algorithms : Regression, Classification, Clustering, Deep Learning etc.
Soft Skills :
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
(ref:hirist.tech)
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