Machine Learning Engineer, Platform

Posted 2024-10-21

💎 Seniority level: Senior, 5+ years of industry experience

📍 Location: United States

💸 Salary: 200000 - 230000 USD per year

🔍 Industry: Event ticket industry

⏳ Experience: 5+ years of industry experience

🪄 Skills: AWSDockerPythonSQLDynamoDBKafkaMachine LearningPyTorchSnowflakeAirflowgRPCRedis

5+ years of industry experience.
Proven track record in designing and implementing mission-critical, high-reliability systems with rapid deployment.
Outstanding programming proficiency, with particular expertise in Python.
Strong working knowledge of AWS or equivalent cloud platforms.
Hands-on experience with industry-standard tools and technologies (e.g., Kafka, Docker, gRPC, DynamoDB, Redis, Temporal, Snowflake, Airflow, SQL).
Keen interest in machine learning and its associated technologies (such as PyTorch, Scikit-Learn, XGBoost, Jupyter), preferably with some practical experience.
Ability to collaborate effectively across teams and communicate with key stakeholders.
A proactive self-starter with a strong ability to learn quickly and work independently.

Collaborate with Machine Learning Engineers and Data Scientists to understand their platform needs and translate them into powerful, generalized solutions.
Own existing platform systems and develop the next generation of tools (e.g. training platform, feature platform, inference platform).
Architect a platform that boosts overall model iteration speed and allows Machine Learning Engineers and Data Scientists to work in a self-serve manner.
Improve the reliability around all components of an ML platform capable of powering critical product features used by millions of users.

Posted 2024-10-16

📍 USA

🧭 Full-Time

💸 180265 - 212000 USD per year

🔍 Cryptocurrency and Blockchain

Experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.
Working knowledge in one or more of the following: data mining, information retrieval, advanced statistics or natural language processing, computer vision.
Exhibit core cultural values: add positive energy, communicate clearly, be curious, and be a builder.

Investigate and harness cutting-edge machine learning methodologies, including deep learning, large language models (LLMs), and graph neural networks to address diverse challenges.
Develop and deploy robust, low-maintenance applied machine learning solutions in a production environment.
Create onboarding codelabs, tools, and infrastructure to democratize access to machine learning resources across Coinbase.

Data MiningMachine LearningData mining

Posted 2024-10-16

🔧 Requirements