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Senior AI/ML Data Engineer - Short-Term Contract (Enterprise Deployment Readiness)

Budget: $60.0 - $90.0 HOURLY / PART_TIME ⭐ 0.00 (0) Canada

pytorch, python, machine-learning, tensorflow, etl-pipelines, snowflake, devops, artificial-intelligence

We are preparing to deploy our AI/ML product into enterprise environments and need a highly experienced Senior AI/ML Data Engineer to conduct a full architectural audit and implement critical fixes before go-live. This is a focused, short-term engagement with clear deliverables. What You'll Do Perform a comprehensive architectural audit of our existing AI/ML data pipeline and infrastructure Identify bottlenecks, scalability gaps, security vulnerabilities, and reliability issues that could impact enterprise deployments Implement fixes and improvements based on audit findings Ensure the system meets enterprise-grade standards: high availability, data governance, access controls, observability, and compliance readiness Provide clear documentation of the current architecture, issues found, and changes made Deliver a prioritized remediation report with actionable recommendations Required Skills & Experience 6+ years of hands-on experience in AI/ML engineering and data infrastructure Deep expertise in ML pipeline architecture (training, serving, monitoring) Strong experience with cloud platforms (AWS / GCP / Azure) at enterprise scale Proficiency in Python and data engineering frameworks (Spark, Kafka, Airflow, dbt, or similar) Familiarity with MLOps practices, CI/CD for ML, model versioning, feature stores Experience with enterprise security requirements: RBAC, SSO, audit logging, data encryption Ability to read, audit, and refactor existing codebases quickly Strong written communication, you'll be expected to document findings clearly Nice to Have Experience with LLM or generative AI product deployments Knowledge of compliance frameworks (SOC 2, GDPR, HIPAA) Prior work on enterprise SaaS or B2B AI product launches Engagement Details Type: Short-term contract (fixed-price or hourly, open to discussion) Duration: Estimated 4-8 weeks depending on scope Availability: Must be able to start within a week Communication: Regular check-ins and progress updates expected How to Apply Please include the following in your proposal: A brief description of a similar architectural audit or enterprise deployment you've led Your approach to assessing an unfamiliar ML system quickly Your estimated timeline and hourly rate or fixed-price bid We're moving fast and want someone who can hit the ground running. Senior-level only, no agencies, please.
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