Data & AI Systems Engineer at Turing

Data & AI Systems Engineer | Contractor (40 hrs/week) | Fully Remote | 9-Month Contract

Turing — the world's leading AI research accelerator based in San Francisco — is seeking a skilled Data & AI Systems Engineer to design, validate, and optimize cloud-based data systems, migration workflows, and AI-driven applications. This is a fully remote contractor role with an expected start date of next week.

About Turing

Turing partners with frontier AI labs and global enterprises to accelerate AI research and transform proof-of-concept systems into reliable, high-impact production solutions. Our expertise spans coding, reasoning, STEM, multilinguality, multimodality, and AI agents.

Key Responsibilities

• Design and support data migration workflows across cloud platforms (AWS, GCP, Azure)
• Plan and execute data migration strategies, evaluating trade-offs such as online vs. offline approaches, performance, and scalability
• Build and maintain ETL/ELT pipelines and workflows in distributed environments
• Integrate and evaluate LLM and Generative AI components within existing workflows
• Execute system testing and validation — including edge case identification, failure analysis, and cross-system debugging
• Ensure data integrity, consistency, and performance across all systems
• Document findings, insights, and recommendations clearly for technical and non-technical stakeholders
• Collaborate with cross-functional teams spanning engineering, data, and product

Required Qualifications

• Hands-on experience with cloud platforms (GCP, AWS, or Azure) and associated data/storage systems
• Strong understanding of data migration processes and associated trade-offs
• Experience with data pipelines, ETL/ELT workflows, or distributed systems
• Practical exposure to LLMs and Generative AI (prompting, evaluation, or integration)
• Background in system testing, validation, or QA
• Strong debugging and analytical problem-solving skills
• Excellent written communication skills for stakeholder documentation

Nice to Have

• Background in storage administration, SRE, or cloud infrastructure operations
• Experience with MLOps, model evaluation frameworks, or AI testing workflows
• Familiarity with Google Cloud Storage (GCS) or similar platforms
• Experience working in Agile environments with cross-functional teams

Engagement Details

• Commitment: 40 hours/week with a minimum 4-hour overlap with PST
• Type: Contractor/Freelancer (no medical or paid leave benefits)
• Duration: 9 months, starting next week

Why Work With Turing?

• Fully remote work environment
• Opportunity to contribute to cutting-edge AI projects with leading LLM companies
• Potential for contract extension based on performance and project needs