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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