Senior Machine Learning Developer

Job Description

As a Senior ML Developer at the company, you’ll spearhead the operationalization of advanced machine learning (ML), User Behavior Analytics (UBA) and GenAI solutions within SIAI (Security Insights and AI) team. In this role, you’ll address the escalating threats in our global digital landscape by leveraging ML and Big Data technologies to model and predict behaviors, enabling proactive threat detection and response.

You may also contribute to next‑gen autonomous/semi‑autonomous AI platforms, integrating large language models (LLMs) and GenAI to enhance detective/preventive controls, operational efficiency, and regulatory compliance.

You’ll guide design process, and help deploy scalable ML pipelines/agentic systems to deliver production‑grade AI solution for Cyber, Fraud, Risk, and Security utilizing on‑prem/cloud‑native tools (GPU AI Farm, Neo4j, Kubernetes, Docker, AWS/Azure) to maintain robust, secure, and compliant production environments.

• Engineer and maintain scalable data pipelines and workflows using PySpark, AWS Sage Maker, Airflow, Jupyter Hub, RunAI, Neo4j.
• Build pipeline to integrate ML/UBA detections into a graph knowledgebase (Neo4j) to enable event correlation and run analytical queries.
• Optimize Spark job performance through advanced tuning, resource management, and cost‑efficient scalability. Deploy batch and real‑time inference models with robust monitoring.
• Deploy, manage, and optimize ML and Agentic applications across multiple platforms such as Cloudera Data Lake, Neo4j Graph DB, AWS, Open Shift Container Platform (OCP), using Helios on Actions CI/CD pipeline.
• Apply and advocate best practices in secure coding and MLOps CI/CD automation (Docker, Kubernetes, Open Shift, Git Hub Actions, Jenkins), traceability (Langfuse) and observability (Prometheus, Grafana).
• Contribute to code reviews, collaborate with data scientists and engineers, front and backend engineers and ML engineers, and maintain clear technical documentation.
• Champion best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring, fallback mechanisms, and secure deployment in regulated environments.

• 2+ years of experience, and advanced programming skills in Python, PySpark, Unix Scripting, SQL, PyTorch etc.
• Strong experience building data pipelines and APIs with Spark, Airflow, Neo4j, SQL (Snowflake, Postgres), and No
  
  SQL (MongoDB); experience with REST, FastAPI/Django.
• Hands‑on experience with Neo4j and Cypher graph query language or other similar graph DB.
• Foundational knowledge of general Machine Learning concepts both in theory and application and some experience with advanced topics such as Deep Learning, Agentic AI and Agent Orchestration.
• Experience with data preprocessing, image processing, hyperparameter optimization, code optimization, feature importance analysis, transfer learning, and anomaly/outlier detection.
• Experience developing CI/CD pipeline for AI/ML models, deploying, and supporting models in production.

• Familiarity with AWS cloud environment services (Lambda, Sage Maker, Bedrock, etc).
• Hands‑on experience deploying LLMs, RAG systems, agent orchestration frameworks (e.g., Lang Chain, CrewAI, Auto Gen), or agentic AI into production, and context engineering for autonomous workflows.
• Familiarity with at least one workflow/AI agent orchestration platform like CrewAI, Lang Graph, N8N, etc.
• Understanding of modern observability stacks (Grafana, Prometheus, Open Telemetry) and secure coding practices (SAST/DAST).

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
• Leaders who support your development through coaching and managing opportunities.
• Ability to make a difference and lasting impact.
• Work in a dynamic, collaborative, progressive, and high‑performing team.
• Opportunities to take on progressively greater accountabilities.
• Access to a variety of job opportunities across business and geographies.

AWS Cloud Computing, Big Data Technologies, Data Science, Deep Learning, Generative AI, Generative AI Agents, GraphDB, Kubernetes, Machine Learning (ML), Neo4j Graph Database, PySpark, Python (Programming Language), RAG Pipeline, Structured Query Language (SQL).

16 YORK ST, TORONTO, Canada