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AI / ML Engineer

AI / ML Engineer
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Edmonton
CAD 80.000 - 120.000
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AI / ML Engineer

Zinkworks
Edmonton
CAD 80.000 - 120.000
Descripción del empleo
About Zinkworks

At Zinkworks, we’re transforming industries by creating cutting-edge solutions that fuse AI, ML, and intelligent automation into real-world applications. We're passionate about innovation, quality, and building high-performance teams that drive impactful change across telecommunications, finance, and emerging tech.

About the Role

We are looking for an experienced and motivated AI/ML Engineer to join our Solutions & Innovation team. This role involves designing and implementing AI models for proof-of-concepts and project solutions within two key verticals: capital markets and telecom networks.

You’ll work on a diverse range of use cases, including anomaly detection in RAN (Radio Access Network) time-series data, network optimization, and time-series modeling in financial systems. Your work will be instrumental in helping our clients—ranging from telecom operators to global banks—leverage advanced AI/ML capabilities for real-time insights and predictive intelligence.

Key Responsibilities

  • Model Development & Experimentation
    • Design, build, and refine AI/ML models using architectures such as LSTM, Transformer, and GCN (Graph Convolutional Networks).
    • Apply anomaly detection techniques (e.g., Isolation Forest, statistical methods) to multivariate time-series data.
  • Data Engineering & Processing
    • Work with structured and semi-structured data from telecom and financial systems.
    • Develop data ingestion and transformation pipelines using GCP services (e.g., Cloud Functions, BigQuery).
  • Deployment & Integration
    • Deploy scalable models to production using GCP tools such as Vertex AI and Cloud Run.
    • Develop REST APIs to expose inference services for integration with client systems.
  • Collaboration & Delivery
    • Collaborate with cross-functional teams including solution architects, cloud engineers, and domain experts.
    • Participate in client workshops and technical governance for PoC delivery and feedback incorporation.
  • Monitoring & Validation
    • Define and track model evaluation metrics (e.g., F1-score, ROC-AUC, RMSE).
    • Implement logging, monitoring, and retraining strategies as needed.

Required Skills and Experience

  • Strong proficiency in Python, with experience using ML frameworks such as TensorFlow or PyTorch.
  • Solid understanding of time-series modeling, anomaly detection, and multivariate data analysis.
  • Hands-on experience with Google Cloud Platform (GCP)—especially Vertex AI, BigQuery, Cloud Functions, and Cloud Run.
  • Familiarity with RESTful API development and serving ML models in production.

Preferred Qualifications

  • Experience working with one or more of the following:
    • Telecom KPIs (e.g., latency, throughput, jitter, SINR)
    • Capital markets datasets (e.g., trade logs, FIX message flows)
  • Experience with Graph Neural Networks and Transformer-based models.
  • Exposure to OSS/BSS systems, RAN telemetry, or network optimization domains.
  • Familiarity with containerization and CI/CD workflows (e.g., Docker, GitHub Actions).
  • Prior experience in financial services, especially around trade surveillance or back-office analytics.
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* El índice de referencia salarialse calcula en base a los salarios que ofrecen los líderes de mercado en los correspondientes sectores. Su función es guiar a los miembros Prémium a la hora de evaluar las distintas ofertas disponibles y de negociar el sueldo. El índice de referencia no es el salario indicado directamente por la empresa en particular, que podría ser muy superior o inferior.

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