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Senior Staff Data Engineer - AI Solutions

Circle

Washington (District of Columbia)

On-site

USD 200,000 - 258,000

Full time

10 days ago

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Job summary

Join a forward-thinking company at the forefront of financial technology as a Senior Staff Data Engineer specializing in AI solutions. In this pivotal role, you will design and develop innovative data architectures and pipelines that empower AI initiatives, enhancing decision-making across the organization. Collaborate with cross-functional teams to implement scalable and efficient data solutions, ensuring high-quality data access for AI model training. This role offers a unique opportunity to lead the way in shaping the future of AI, driving impactful change in a diverse and inclusive work environment. If you are passionate about data and AI, this is your chance to make a significant impact.

Qualifications

  • 10+ years of experience in data engineering focused on AI solutions.
  • Advanced proficiency in SQL and data warehouse technologies.
  • Strong coding skills in Python or Scala with AI frameworks.

Responsibilities

  • Design and implement robust data architectures for AI model training.
  • Develop and maintain feature stores for dynamic, high-quality features.
  • Collaborate with data scientists to optimize data flows for AI models.

Skills

Data Engineering
SQL
Python
Scala
Machine Learning
Data Governance
Collaboration

Education

Bachelor's Degree in Computer Science or related field
Master's Degree in Data Science or related field

Tools

BigQuery
Snowflake
Databricks
TensorFlow
PyTorch
Airflow
Hadoop
Kafka
AWS
GCP

Job description

Senior Staff Data Engineer - AI Solutions

Join to apply for the Senior Staff Data Engineer - AI Solutions role at Circle

Senior Staff Data Engineer - AI Solutions

1 week ago Be among the first 25 applicants

Join to apply for the Senior Staff Data Engineer - AI Solutions role at Circle

Circle is a financial technology company at the epicenter of the emerging internet of money, where value can finally travel like other digital data — globally, nearly instantly and less expensively than legacy settlement systems. This ground-breaking new internet layer opens up previously unimaginable possibilities for payments, commerce and markets that can help raise global economic prosperity and enhance inclusion. Our infrastructure – including USDC, a blockchain-based dollar – helps businesses, institutions and developers harness these breakthroughs and capitalize on this major turning point in the evolution of money and technology.

What You’ll Be Part Of

Circle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible and diverse work environment where new ideas are encouraged and everyone is a stakeholder.

What You’ll Be Responsible For

As a Senior Staff Data Engineer specializing in AI solutions, you will drive the design and development of innovative data architectures and pipelines that support the training of AI models and enhance the integration of data into AI platforms. Your expertise will play a crucial role in advancing our AI initiatives and enabling smarter decision-making across the organization. You will collaborate with cross-functional teams to ensure that high-quality, scalable, and efficient data solutions are implemented, laying the foundation for AI-powered insights and products.

What You'll Work On

  • Design and implement robust data architectures and ETL/ELT pipelines specifically tailored for AI model training and data ingestion into AI platforms.
  • Develop and maintain feature stores to serve as centralized repositories for dynamic, high-quality features crucial for training and serving AI models. Ensure easy access to and versioning of features for data scientists and AI engineers.
  • Collaborate with data scientists and AI engineers to understand data requirements, optimize data flows, and enable seamless access to high-quality data for model training.
  • Build automation and monitoring capabilities around feature engineering processes, including real-time feature computation and batch processing, to enhance model training efficiency.
  • Implement data governance and quality assurance practices to ensure the integrity, accuracy, and reliability of the data and features used in AI applications.
  • Explore and integrate new data technologies and tools that enhance data processing efficiencies and support AI initiatives.
  • Mentor and lead junior data engineering staff, promoting guidelines and innovative solutions within the data engineering community.
  • Collaborate with stakeholders across product, engineering, and analytics teams to identify and prioritize opportunities to drive AI initiatives and improve business outcomes.

What You’ll Bring To The Team

  • 10+ years of experience in data engineering, with a focus on building data solutions for AI and machine learning applications.
  • Advanced proficiency in SQL and expertise in data warehouse technologies such as BigQuery, Snowflake, or Databricks, enabling effective data management and optimization.
  • Strong coding skills in programming languages such as Python or Scala, with experience in frameworks commonly used for machine learning and AI (e.g., TensorFlow, PyTorch).
  • Extensive experience in designing and implementing scalable data pipelines and architectures for large-scale AI applications, demonstrating proficiency in workflow orchestration tools (e.g., Airflow, Dagster).
  • Proven experience creating and maintaining feature stores, ensuring the efficient delivery and retrieval of features for model training and real-time inference.
  • Knowledge of data technologies and platforms (e.g., Hadoop, Kafka) and experience with cloud services (AWS, GCP, Azure) to support data processing and storage needs.
  • Thought leadership and autonomy in defining our strategy for how our AI platform will interact with our data ecosystem (data platform and assets).
  • Strong multi-stakeholder partnership and collaboration skills, with the ability to effectively partner with:
    • Data Platform: Defining requirements for a feature store and other data platform features.
    • AI Platform: Defining data access patterns for the different AI platform components to ensure seamless integration.
    • Data Governance: Ensuring compliance with our data governance policies—such as access control and purpose policies—through programmatic enforcement.
Join us in shaping the future of AI through innovative data solutions and feature stores that empower our organization to harness the full potential of our data assets.

Circle is on a mission to create an inclusive financial future, with transparency at our core. We consider a wide variety of elements when crafting our compensation ranges and total compensation packages.

Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.

Base Salary Range: $200,000 - $257,500

We are an equal opportunity employer and value diversity at Circle. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Additionally, Circle participates in the E-Verify Program in certain locations, as required by law.

Should you require accommodations or assistance in our interview process because of a disability, please reach out to accommodations@circle.com for support. We respect your privacy and will connect with you separately from our interview process to accommodate your needs.

Seniority level
  • Seniority level
    Mid-Senior level
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Information Technology

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