Ideogram is hiring a Applied Machine Learning in Toronto!
Ideogram is a Toronto-headquartered generative media company building proprietary models and AI-native creative tools for design. With nearly $100M raised and a fast-growing team, it pairs frontier research with consumer and enterprise products. This Applied Machine Learning role sits between research and product: you would turn generative models into shipped features across Ideogram’s app and API, working closely with researchers, engineers, infrastructure teams, product partners, and clients. The position emphasizes rapid experimentation, rigorous evaluation, dataset construction, fine-tuning, and reliable deployment for creative use cases such as text-to-image, image-to-text, image enhancement and editing, and multimodal workflows. You would also help define client success measures around quality, latency, and cost, and lead early 0-to-1 projects that shape how Applied ML serves enterprise customers. The team describes itself as flat, fast-moving, and highly collaborative, with strong ownership and mentorship. Compensation includes equity, health coverage, retirement matching, vacation, and in-office perks at the Toronto HQ near Union Station.
Key responsibilities
- Convert frontier generative-model research into production features for the first-party app and API.
- Design and run experiments, benchmarks, evaluation corpora, and failure-mode analyses.
- Curate, label, and clean datasets used for training, fine-tuning, and evaluation.
- Fine-tune and deploy models for text-to-image, image-to-text, image enhancement, editing, and multimodal use cases.
- Define client success metrics for quality, latency, and cost, then iterate toward measurable improvements.
- Partner with research, engineering, infrastructure, product, and clients to ship scalable ML systems.
- Lead 0-to-1 projects that establish Applied ML enterprise practices.
- Contribute to safety, monitoring, and reliability of deployed systems.
Key requirements
- 1+ years of experience building and shipping machine learning products.
- Backend development skills in Python with PyTorch or JAX.
- Ability to design benchmarks and evaluation metrics, run error analyses, and debug numerical stability across data, training, and inference.
- A track record of taking ML features from idea through evaluation to production with measurable quality, latency, or cost gains.
- Comfort curating, labeling, and cleaning datasets and designing evaluation corpora.
- Familiarity with modern deep learning concepts such as transformers, diffusion models, and encoders.
- Strong collaboration with product teams and pragmatic, fast iteration.
- Ownership, urgency, curiosity, and strong communication skills in a startup environment.
- Seniority: Mid-level (1+ years)
- Work mode: In-office (Toronto HQ)
- Key skills: Python, PyTorch, JAX, Diffusion models, Transformers, Multimodal ML, Model evaluation, Dataset curation, Production ML, Fine-tuning
Want more jobs?
Join our mailing list to receive updates about new data science and Applied Machine Learning jobs.
