[Hiring] Senior Machine Learning Engineer @Smartverify

Role Description

This is a role for someone who trains models, not someone who calls them. We are building classification and detection systems from scratch, including:

• Fine-tuned transformers
• Entity detection over structured and unstructured content
• Behavioral scoring against a self-defined taxonomy

If your recent work involves retrieval-augmented generation, prompt engineering, agent orchestration, or integrating a foundation model API, this is a different discipline and we would be wasting your time.

If you have owned a classifier in production, from data through training through evaluation through the retraining loop, please consider applying.

Qualifications

• 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
• Authorized to work in Canada or the United States, located in British Columbia or the Seattle area

Requirements

• 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

Benefits

• Remote work within the Seattle area or British Columbia, with periodic in-person time with the team
• Existing authorization to work in the United States is required
• Ability to sponsor work visa and PR in Canada
• Below-market base plus meaningful early-stage equity
• Specific compensation discussions early in the process

Company Description

SmartVerify is building the data egress control plane for enterprise AI. We sit 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. You have freedom to update the spec as you come in and evaluate the goals. You would be the only ML engineer on staff, reporting directly to the founder, who has a background in this space, with a co-op available to own the evaluation harness and pipeline QA under your direction.

What You Would Own

• The behavioral classification model: multi-class classification of AI agent query intent against our internal taxonomy
• PII and PHI detection over query content and returned data
• Behavioral risk scoring, combining deterministic request signals with model-derived signals
• Model training, serving, and versioning on SageMaker
• The evaluation harness, drift detection, and retraining loop
• The classification output contract that downstream audit, enrichment, and dashboard consumers depend on

Who Does Well Here

• You have shipped a model that other systems depended on
• You are honest about model limitations
• You can read an architecture document, disagree with part of it, and articulate your reasoning
• You are comfortable being the only person in the company who understands this layer
• You want ownership more than you want a large team

The Stack

• Intelligence layer: PyTorch, Hugging Face Transformers, SageMaker training and inference, evaluation and drift tooling
• Infrastructure: AWS, EKS, Terraform, Helm, Prometheus, Grafana