$50 - $75/hr
Full-time
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Job description
Data Infrastructure Engineer (Rust) - High Performance Computing
$50-75/hr Remote Freelance CODING
Senior Rust Engineer — AI Data Infrastructure
What if your deep expertise in Rust could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a Senior Rust Full-Stack Engineer to design and build the high-performance data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on.
This is a fully remote, flexible contract role for elite engineers who care about correctness, performance, and building systems that actually scale. If you've spent years thinking about memory layouts, concurrency patterns, and squeezing every cycle out of production systems — this is the role for you.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
What You'll Do
- Design, build, and optimize high-performance Rust systems supporting large-scale AI data pipelines and evaluation workflows
- Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
- Hunt down and eliminate bottlenecks — profiling, identifying edge cases, and implementing durable, scalable fixes
- Improve reliability, safety, and performance across production Rust codebases
- Collaborate with data, research, and engineering teams to support model training and evaluation pipelines
- Participate in synchronous design reviews to iterate on architecture and implementation decisions
Who You Are
- 5+ years of professional, production Rust experience — this is a must
- Deep expertise in data parallelism and concurrency patterns to maximize CPU saturation
- Strong command of memory layout, SIMD optimizations, and heap allocation strategies — you know how to find and fix performance bottlenecks
- Native or fluent English speaker with clear written and verbal communication skills
- Able to commit 20–40 hours per week with reliable availability
- Self-directed and confident making high-impact engineering decisions independently
Nice to Have
- Prior experience with data annotation pipelines, data quality systems, or model evaluation infrastructure
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Experience building distributed systems or developer tooling
- Background working with or alongside research engineering teams
Why Join Us
- Work on production systems that directly power cutting-edge AI research and development
- Fully remote and flexible — structure your week around your best working hours
- Freelance autonomy with the depth and impact of meaningful, high-complexity engineering work
- Collaborate with world-class engineers and researchers at leading AI labs
- Potential for ongoing work and contract extension across new projects as they launch
Apply now
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Senior Infrastructure Engineer?
A: To succeed as a Senior Infrastructure Engineer, key technical skills include expertise in cloud computing platforms (e.g., AWS, Azure, Google Cloud), proficiency in containerization (e.g., Docker), and in-depth knowledge of networking protocols and security measures. Soft skills such as strong communication, problem-solving, and leadership abilities are also crucial, as they enable effective collaboration with cross-functional teams and the ability to drive infrastructure modernization initiatives. By combining these technical and soft skills, Senior Infrastructure Engineers can drive business growth, improve operational efficiency, and establish themselves as trusted technical leaders within their organizations.
Q: What is the career path for a Senior Infrastructure Engineer?
A: A Senior Infrastructure Engineer's typical career progression involves starting as an Infrastructure Engineer, then advancing to a Senior Infrastructure Engineer, and eventually moving into leadership roles such as Technical Lead or Infrastructure Architect. Key opportunities for skill development include cloud computing, containerization, and DevOps practices, as well as staying up-to-date with emerging technologies like artificial intelligence and machine learning. Long-term career prospects may include transitioning into management roles, such as IT Director or CTO, or pursuing specialized roles like Cloud Security Engineer or Data Center Manager.
