Lead Engineer, MLOps

2 weeks ago

New York, United States Code and Theory Full time

Our Ai/ML engineering team ensures Code and Theory delivers innovative, immersive web experiences that delight our clients and their customers. We are always striving to balance the demanding nature of working on cutting-edge technologies with the real-world demands of high performance, high security, and accessibility. Working in collaboration with our multi-disciplinary engineering, design, and quality assurance teams, you will build software that solves real-world problems for incredible clients.

We are seeking an experienced Lead ML+DevOps Engineer. The ideal candidate will have strong expertise in cloud deployment, containerization, and related technologies, and will play a crucial role in the scalability and reliability of our AI/ML infrastructure. You’ll be in a high-visibility role, working with all sorts of clients both internally and externally to deliver scalable, precise, and – most importantly – interesting machine learning solutions. Our work stretches from audience segmentation to dynamic content generation, from spell-checking to large language modeling and beyond.

WHAT YOU’LL DO:

  1. Design and implement MLOps pipelines to ensure consistency across the organization.
  2. Configure and manage cloud-based resources (e.g., AWS, GCP, Azure) to support AI/ML workloads, leveraging containerization as needed.
  3. Automate model deployment and management through scripts and tools to streamline the process.
  4. Collaborate with data scientists and engineers to understand their requirements and develop tailored MLOps solutions.
  5. Monitor and optimize AI/ML infrastructure performance by analyzing system performance and identifying bottlenecks.
  6. Stay up-to-date with industry trends and best practices, applying this knowledge to improve our organization's MLOps capabilities.

WHAT YOU’LL NEED:

  1. Extensive experience in deploying machine learning models to cloud environments.
  2. Strong expertise in Docker container orchestration.
  3. Proficiency in Terraform for infrastructure as code (IaC) and cloud resource management.
  4. Hands-on experience with streaming data platforms (e.g., Kafka, Kinesis).
  5. Solid understanding of data cleaning, transformation, and ETL processes.
  6. Experience with CI/CD tools and pipelines (e.g., Jenkins, GitLab CI).
  7. Strong programming skills in Python. Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) is a plus.
  8. Excellent problem-solving skills and the ability to think critically and creatively.
  9. Strong communication skills with the ability to convey technical concepts to non-technical stakeholders.

ABOUT US

Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. With a remote-first approach to our people, we have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Mediacurrent, Rhythm, and TrueLogic.

Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.

The Code and Theory network comprises nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.

The target range of base compensation for this role is $140k-$180k. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.

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