Applied Machine Learning
Role Overview
The Applied ML Engineer will bridge research and product by turning generative models into production features for Ideogram’s application and API.
The role involves working with research, engineering, infrastructure, product teams, and clients to deliver reliable and scalable ML systems.
Key Skills for This Role
Full Job Posting
About Ideogram
Ideogram builds generative media models and AI-native creative workflows intended to make high-quality design accessible to everyone.
The company is headquartered in Toronto and is growing its team while developing products for creative users and enterprise customers.
The Opportunity
The Applied ML Engineer will bridge research and product by turning generative models into production features for Ideogram’s application and API.
The role involves working with research, engineering, infrastructure, product teams, and clients to deliver reliable and scalable ML systems.
Core Work
- Fine-tune and deploy models for text-to-image, image-to-text, image enhancement, image editing, and multimodal applications.
- Build evaluations and datasets, define client success metrics, and contribute to system safety, monitoring, and reliability.
- Lead zero-to-one projects that establish applied machine learning practices for enterprise use cases.
What We’re Looking For
- At least 1 year of experience building and shipping ML products.
- Backend coding ability in Python, PyTorch, or JAX.
- Experience with benchmarks, evaluation metrics, error analysis, numerical stability, and production ML feature delivery.
- Comfort with dataset curation, labeling, cleaning, evaluation corpora, and failure-mode analysis.
- Familiarity with transformers, diffusion models, encoders, and modern deep learning.
- Strong communication, interpersonal skills, ownership, urgency, curiosity, and ability to learn quickly.
What We Offer
- Competitive compensation and equity, four weeks of vacation, and comprehensive health, vision, and dental coverage from day one.
- RRSP or 401(k) employer matching up to 4%, high-quality tools and technology, and access to compute and other resources for justified experiments.
- Toronto headquarters perks include proximity to Union Station and daily in-office lunches and dinners.
- The company supports autonomy, experimentation, learning, growth, and mentorship.
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