We seek a highly skilled and experienced Lead Machine Learning Engineer with extensive expertise in multimodal generative AI models, cross-modal architectures, and multimodal fusion techniques. The ideal candidate will not only have a strong technical background spanning text, vision, audio, and video modalities, but also the drive to mentor, educate, and advocate for the adoption of new and emerging technologies.
WHAT YOU'LL NEED
- 7+ years experience in machine learning engineering, with at least 2+ years focussed on generative AI or multimodal systems
- Proven experience developing and deploying multimodal generative AI systems with deep understanding of architectures that bridge multiple modalities (text-to-image, image-to-text, text-to-video, audio-visual models, etc.)
- Strong expertise in vision models and architectures including diffusion models, vision transformers, and multimodal embeddings
- Experience with large language models and their integration with visual and audio modalities
- Experience with multimodal retrieval systems and vector databases
- Hands-on experience with generative models across modalities including text generation, image synthesis, video generation, and audio/speech synthesis
- Demonstrated ability to lead and mentor a team of machine learning engineers and data scientists, fostering a culture of innovation and technical excellence
- Excellent communication and presentation skills, with the ability to articulate complex multimodal concepts clearly to both technical and non-technical audiences
- Professional experience developing Python libraries for machine-learning applications. Strong background in PyTorch, HuggingFace Transformers/Diffusers, and specialized libraries (e.g., Stable Diffusion, OpenAI CLIP, timm, torchaudio, torchvision)
- Strong problem-solving skills and the ability to think critically and creatively about novel multimodal applications
NICE TO HAVE
- A track record of published research in reputable journals or conferences (NeurIPS, ICML, CVPR, ICCV, etc.)
- Understanding of prompt engineering and guidance techniques for generative models
- Experience with model fine-tuning, LoRA, and efficient adaptation methods
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.