Senior Machine Learning Engineer, West Coast

Smartverify•,

34d•CA$120,000 - CA$160,000•Remote

About The Position

We are building classification and detection systems from scratch, including fine-tuned transformers, entity detection over structured and unstructured content, and behavioral scoring against a defined taxonomy. This role is for someone who trains models and has owned a classifier in production, from data through training through evaluation through the retraining loop. SmartVerify is building the data egress control plane for enterprise AI, sitting inline between AI agents and enterprise data, inspecting every query, enforcing policy in real time, and producing an immutable audit trail. This is a greenfield build against an existing spec, offering the opportunity to update the spec and evaluate goals. The role reports directly to the founder and will have a co-op available to assist with evaluation harness and pipeline QA.

Requirements

Production ML ownership: models you trained, deployed, monitored, and retrained in a live system
Transformer fine-tuning for text classification (BERT family, DistilBERT, or equivalent)
Sequence labelling or named entity recognition for structured entity detection
Python, PyTorch, Hugging Face Transformers
Evaluation rigour: ability to explain threshold choices and trade-offs
Comfort working from a written design spec rather than waiting for direction
Authorized to work in Canada or the United States, located in British Columbia or the Seattle area
Must be able to attend an in-person onsite interview

Nice To Haves

Bootstrapping labels through weak supervision, LLM-assisted labelling, or active learning
Anomaly or behavioural detection with sparse or absent labels
SageMaker training jobs and inference endpoints
Regulated domain experience: HIPAA, PCI DSS, GDPR, or SOC 2
Fraud, abuse, or security detection background
Distillation or quantisation to hold an inference latency budget
Kinesis, Kafka, or other streaming pipelines
SQL and query structure parsing
Mentoring a junior engineer or co-op

Responsibilities

Own the behavioral classification model: multi-class classification of AI agent query intent against our internal taxonomy, producing labels, confidence, and supporting evidence.
Own PII and PHI detection over query content and returned data, including span-level identification suitable for audit evidence.
Own behavioral risk scoring, combining deterministic request signals with model-derived signals.
Manage model training, serving, and versioning on SageMaker within the asynchronous inspection path.
Oversee the evaluation harness, drift detection, and retraining loop, with a co-op supporting the harness work.
Define the classification output contract that downstream audit, enrichment, and dashboard consumers depend on.