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Machine Learning Engineer, Data
4 months ago
Location: Seattle, WA OR Los Angeles, CA (Hybrid)
The Company Metropolis is an artificial intelligence company for the real world. Metropolis' computer vision platform enables people to transact in the physical world with even greater ease than we experience online. Today, we are reimagining parking. Because it's important, it's everywhere, and impacts everyone – enabling millions of consumers to just "drive in and drive out" – that's it. Tomorrow, we will power "checkout-free" experiences anywhere you go. The Role We are seeking a Machine Learning Engineer to play a key role in accelerating our model development through data innovation. As a key member of our Engineering organization, you'll be instrumental in designing and building a robust generative data engine and algorithms that fuel machine learning models. This role involves a unique blend of technical expertise in Data and Machine Learning, innovative thinking, and a passion for data-driven solutions. Your mission will be to connect the dots between data and machine learning models through intelligent algorithms and automation. You'll be responsible for developing and maintaining a scalable Machine Learning data solution that underpins our models, ensuring the delivery of optimal solutions to our customers. Responsibilities- Work with the machine learning team to perform state-of-the-art research, train, and optimize machine learning algorithms.
- Design, implement, and maintain active learning algorithms and generative vision models to ensure cost efficient data sampling and learning.
- Maintain and revisit innovative methodologies to curate high quality data and annotations.
- Design, implement, and maintain the machine learning data pipelines and infrastructure.
- Work with technologies like AWS, SQL/NoSQL databases, Kafka, Airflow, and NVIDIA Triton, ensuring efficient and effective use of these tools.
- Collaborate with other Engineering and Product teams to define requirements and facilitate the smooth deployment of software into production.
- Play a vital role in the entire development lifecycle, from concept and requirement identification to implementation.
- Implement best practices in automation, testing, and deployment to foster rapid feature/model development and release.
- Foster a culture that views bugs and production issues as opportunities for improvement.
- Contribute to the hiring and cultural development within Metropolis Engineering.
- Ensure high availability and scalability of Machine Learning systems.
- Collaborate with partners to integrate their products seamlessly into the Metropolis platform.
- MS or BS in Computer Science, Engineering, or a related field, or equivalent work experience.
- 2+ years of experience in machine learning and software engineering, with expertise in computer vision and multi-modal models.
- Proficiency in Python and Machine Learning frameworks (PyTorch/TensorFlow/ONNX/TensorRT)
- Strong experience with cloud services, preferably AWS.
- Proven experience in building and maintaining data pipelines (e.g., Airflow, Mage.ai, Dagster).
- Familiarity with Machine Learning model serving infrastructure and best practices.
- Knowledge of transactional and analytical database technologies.
- Strong understanding of the agile development process and CI/CD pipelines and tools (e.g., Github Actions, Jenkins).
- Excellent communication skills, capable of presenting complex technical information clearly.
- Experience in high-growth, innovative environments is a plus.
