About the role
About the Job
Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. We work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
Position
Senior C++ Full-Stack Engineer — AI Data & Infrastructure
Type: Contract, Remote Commitment: 20–40 hours/week Compensation: Competitive, hourly (based on experience)
Role Responsibilities
- Design, build, and optimize high-performance systems in C++ supporting AI data pipelines and evaluation workflows
- Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
- Improve reliability, performance, and safety across existing C++ codebases
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- Identify bottlenecks and edge cases in data and system behavior, and implement scalable fixes
- Participate in synchronous reviews to iterate on system design and implementation decisions
Qualifications
Must-Have
- Native or fluent English speaker
- Full-stack developer experience with a strong systems programming background
- 5+ years of professional experience writing production C++ (prefer modern standards like C++17 or C++20).
- Deep understanding of computer architecture, SIMD intrinsics, and cache coherency to optimize compute-heavy AI workloads.
- Expertise in lock-free programming and maximizing parallelism using threading libraries.
- Clear written and verbal communication skills for technical leadership.
- Ability to commit 20–40 hours per week.
Preferred
- Prior experience with data annotation, data quality, or evaluation systems
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Experience with distributed systems or developer tooling
Application Process
- Submit your resume
- Complete a short technical screening
- Project matching and onboarding
Aplyr's read
Labelbox is a cutting-edge data training platform focused on enhancing AI capabilities through efficient data annotation. Ideal for tech professionals passionate about AI and machine learning.
What's promising
- •Labelbox offers a robust platform that significantly accelerates AI model training.
- •The company is at the forefront of AI data annotation, a rapidly growing field.
- •Recent roles indicate a strong focus on diverse AI applications and research.
What to watch
- •The niche focus on data annotation may limit broader tech career opportunities.
- •Highly specialized roles might require advanced expertise in AI and machine learning.
- •Potential candidates may face intense competition due to the company's innovative reputation.
Why Labelbox
- •Labelbox uniquely integrates data annotation with AI model improvement.
- •The company emphasizes a forward-deployed engineering approach, embedding engineers directly with clients.
- •Its platform is designed to streamline complex data labeling processes efficiently.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Labelbox
Labelbox is a data training platform that enables organizations to build and manage high-quality training datasets for machine learning applications. By streamlining the data labeling process, Labelbox empowers teams to accelerate their AI initiatives and improve model performance.
