Posting record
Open 6+ days
- Engramme's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Engramme, so its true age is longer.
Last checked Nov 3, 2026.
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Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
Build and deploy ML models for memory retrieval and contextual understanding. Create scalable ML infrastructure that powers intelligent memory systems.
What You'll Do
- Design and implement ML models for memory retrieval and ranking
- Build ML infrastructure and training pipelines
- Deploy and monitor models in production at scale
- Optimize model performance and latency for real-time systems
- Work with vector databases and embedding systems
- Implement MLOps best practices and monitoring
- Collaborate with research team to productionize new algorithms
What We're Looking For
- 4+ years of ML engineering experience
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
- Experience deploying ML models to production
- Knowledge of MLOps, model serving, and monitoring
- Understanding of NLP, embeddings, and retrieval systems
- Experience with cloud platforms (AWS, GCP) and containers
- Strong software engineering fundamentals
- Experience with large-scale data processing
Nice to Have
- Experience with large language models and prompt engineering
- Knowledge of vector databases (Pinecone, Weaviate, Milvus)
- Experience with recommendation systems or search
- Background in information retrieval or ranking systems
- Knowledge of model optimization and quantization
- Experience with real-time ML systems
- Familiarity with transformer architectures
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