10 часов назад
ML Engineer (AI)
160 000 - 180 000CAD
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Engineer (AI): Building machine-learning and applied-AI capabilities for detecting AI agents at runtime, assessing risk, and establishing behavioural baselines in regulated enterprise environments with an accent on telemetry classification, threat detection, and LLM-powered security policy. Focus on designing production ML systems, model deployment and versioning, A/B testing, and low-latency inference over large-scale infrastructure telemetry.
Location: Vancouver, hybrid
Salary: CAD $160,000–$180,000 per year
Company
develops Calico, a network security and observability platform for preventing, detecting, and mitigating security breaches in Kubernetes clusters.
What you will do
- Own the machine-learning and applied-AI capabilities for detecting AI agents at runtime and assessing their risk.
- Build classification models from runtime telemetry, behavioural threat detection, and behavioural baselines.
- Use LLMs to connect security intent with machine-enforceable policy.
- Shape telemetry pipelines, product features, roadmap decisions, model deployment, model versioning, and production A/B testing.
- Design ML systems on top of the existing data infrastructure and collaborate on broader architecture decisions.
Requirements
- 5+ years of professional ML engineering experience, including at least 2 years building and deploying production ML systems.
- Strong knowledge of classical machine learning, including gradient-boosted trees, regression, classification, evaluation, feature engineering, class imbalance, and noisy labels.
- Experience with anomaly detection or time-series modelling.
- Hands-on experience with LLMs for function calling, retrieval-augmented generation, prompt engineering, fine-tuning, and evaluation.
- Python and standard ML tools such as scikit-learn, PyTorch or TensorFlow, and pandas.
- Experience working with large-scale telemetry data using ClickHouse, BigQuery, Snowflake, Spark, or equivalent technologies; excellent written and verbal communication skills.
Nice to have
- Experience in security, infrastructure, or systems-adjacent ML.
- Familiarity with eBPF, kernel telemetry, or low-level systems observability.
- Experience deploying ML models in latency-sensitive paths, including sub-millisecond inference.
- Open-source contributions, model versioning tools, or experience with interpretable ML.
Culture & Benefits
- Small, flat team with high autonomy and end-to-end product ownership.
- Fast planning and shipping with open architecture reviews.
- Direct reporting to the CTO.
- Opportunities to publish research, speak at conferences, and represent in the technical community.
- Full health, vision, and dental benefits in a collaborative and flexible work environment.
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