Collaborate with data scientists and business to augment digital transformation efforts by identifying and piloting use cases. Discuss the feasibility of use cases along with architectural design with business teams and translate the vision of business leaders into realistic technical implementation. At the same time, bring attention to misaligned initiatives and impractical use cases.
Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings. Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools.
Work closely with security and risk leaders to foresee and overturn risks, such as training data poisoning, AI model theft and adversarial samples, ensuring ethical AI implementation and restoring trust in AI systems. Remain acquainted with upcoming regulations and map them to best practice.
WHAT YOU’LL DO:
- Solution Design: Collaborate with cross-functional teams to define AI use cases, gather requirements, and architect end-to-end AI solutions that align with business goals.
- Algorithm Development: Develop and implement machine learning and deep learning algorithms, models, and frameworks to solve intricate problems and enhance system capabilities.
- Data Processing: Oversee data collection, preprocessing, and feature engineering to ensure high-quality input for AI models.
- Model Training and Evaluation: Train and fine-tune machine learning models using large datasets, and rigorously evaluate model performance using appropriate metrics.
- Infrastructure and Tools: Design the AI infrastructure, choose suitable frameworks, libraries, and tools, and ensure scalability, reliability, and efficiency of AI systems.
- Prototyping and POCs: Build rapid prototypes and proof of concepts (POCs) to demonstrate the feasibility and potential of AI solutions.
- Technical Leadership: Provide technical guidance, mentorship, and support to AI development teams, fostering a culture of innovation and collaboration.
- Research and Innovation: Stay abreast of AI trends, emerging technologies, and best practices, and contribute to the company's AI strategy by proposing innovative solutions.
- Deployment and Integration: Lead the deployment of AI solutions into production environments, integrating them with existing systems and workflows.
- Performance Optimization: Continuously optimize AI solutions for speed, efficiency, and accuracy, and address any bottlenecks or issues.
- Documentation: Create comprehensive technical documentation, including design specifications, architecture diagrams, and code comments.
WHAT YOU’LL NEED:
- Proven experience as an AI Engineer, Machine Learning Engineer, Data Engineer or AI Architect, with a track record of successful AI solution design and implementation.
- Strong programming skills in languages such as Python, Java, or C++, and proficiency in AI libraries and frameworks (TensorFlow, PyTorch, scikit-learn, etc.).
- In-depth knowledge of machine learning techniques, algorithms, and model evaluation.
- Familiarity with big data technologies, cloud platforms, and distributed computing.
- Excellent problem-solving abilities and analytical thinking.
- Effective communication skills to collaborate with cross-functional teams and present technical concepts to both technical and non-technical stakeholders.
- Demonstrated ability to lead technical projects, drive innovation, and mentor junior team members.
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 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.
The target range of base compensation for this role is $120k-$150k. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.
