7 дней назад
Data Scientist (AI/ML)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (AI/ML): Building and deploying machine learning and generative AI systems for software supply-chain security, anomaly detection, and developer-facing experiences with an accent on LLM applications, model evaluation, and scalable production workflows. Focus on designing reliable experiments, building agentic systems and retrieval pipelines, and translating research into secure APIs and tools.
Location: Remote in Canada; Toronto is listed as a remote location.
Company
develops software supply-chain management and security solutions, including tools for open-source component management, malware prevention, and DevSecOps.
What you will do
- Lead applied AI projects from prototyping and validation through deployment and measurable business impact.
- Consult with product, engineering, security, and research teams on ML and generative AI use cases.
- Build models and applications for malicious-behavior detection, anomaly detection, fraud analysis, and developer experiences.
- Design evaluation pipelines covering model reliability, accuracy, drift, ground truth, and business impact.
- Translate research into scalable APIs, tools, and workflows that other teams can adopt.
- Communicate technical tradeoffs, mentor peers, and support data privacy and ethical-use practices.
Requirements
- 5+ years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.
- Strong Python skills and experience with Databricks, LLM APIs, and scikit-learn.
- Experience building and shipping ML or generative AI applications from prototype to production-ready workflows.
- Knowledge of LLM ecosystems, prompting, context management, structured outputs, retrieval, and tool use.
- Experience with agentic or multi-step AI workflows using LangGraph, LangChain, Semantic Kernel, or similar frameworks.
- Proficiency with Git, testing, code review, collaborative software development, and large structured and unstructured datasets.
Nice to have
- MLOps experience with MLflow or comparable tooling, reproducible pipelines, CI/CD, serving, and production monitoring.
- Experience operating ML or generative AI systems at scale, including observability, tracing, incident response, and drift detection.
- Experience with AWS SageMaker, Azure ML, Databricks ML, PySpark, or production data pipelines.
- Familiarity with MCP, agent-tool integrations, LLM guardrails, and production safety practices.
- Exposure to cybersecurity, fraud detection, code analysis, software supply-chain security, or SaaS products.
Culture & Benefits
- Remote work in Canada with collaboration across product, engineering, security, and research functions.
- Opportunities to work on applied AI, software supply-chain security, and open-source security research.
- Diversity and inclusion working groups.
- Parental leave policy.
- Paid volunteer time off.
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