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We seek a highly skilled and experienced Lead Machine Learning Engineer with a PhD and extensive expertise in large language models (LLMs), multi-agent systems, and flow engineering. The ideal candidate will not only have a strong technical background but also the drive to mentor and educate our machine learning team and advocate for the adoption of new and emerging technologies.
WHAT YOU'LL DO
WHAT YOU'LL NEED
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. 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, Create Group, 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 is comprised of 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.
Job ID: 135866407
Skills:
Data Modelling, PowerShell, Docker, Terraform, Microsoft Azure, Arm, Kubernetes, Python, DevOps practices, architecture blueprints, dataflows, containerisation, data analytics solutions, Relational Databases, cloud-native principles, AWS PaaS services, infrastructure-as-code, integration diagrams, cybersecurity best practices
Skills:
Java, Apis, Code Analysis, Microsoft Azure, Log Analysis, Python, LangChain, AI-powered applications, end-to-end transaction tracing, Go, vector databases, on-premise networking, agentic workflows, Chat APIs, Search, chatbots, AI assistants, security and audit, RAG pipelines, custom data integration, technical debugging, Indexing
Skills:
ATS, Service Now, Jira, Git, Ansible, Rundeck, Kubernetes, Python, Market Data, ADH, Ads, DACS, RHEL servers, RTDS, DX1
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