Note: The job is a remote job and is open to candidates in USA. Intelliswift, an LTTS Company, is seeking a Software Engineer/Research Engineer to advance next-generation AI systems. The role focuses on designing benchmarks, test suites, automation frameworks, and evaluation pipelines, while collaborating with researchers and engineers to assess and improve AI model performance.
Responsibilities
- Design, implement, and maintain evaluation frameworks for AI and machine learning systems
- Develop benchmarks, test suites, and validation workflows used to measure model performance
- Investigate model behavior, performance discrepancies, and system-level issues through data-driven experimentation
- Build scalable Python-based tooling and infrastructure to support AI research and evaluation
- Collaborate with researchers and cross-functional teams to improve model quality and performance
- Document findings, methodologies, and technical decisions to ensure reproducibility
- Contribute to deployment, monitoring, and operational excellence of AI systems
- Drive engineering best practices around testing, reliability, and code quality
Skills
- • Bachelor's degree in Computer Science, Engineering, Machine Learning, AI, or a related field
- • 1-3 years of experience in AI/ML engineering, research engineering, or software engineering
- • Strong programming skills in Python
- • Hands-on experience training and evaluating machine learning models
- • Experience with PyTorch and modern deep learning frameworks
- • Experience developing benchmarks, validation frameworks, or model evaluation workflows
- • Strong debugging, analytical, and problem-solving abilities
- • Demonstrated experience managing technical projects from implementation through validation and delivery
- • Familiarity with AI-assisted development tools such as Claude Code, Cursor, Codex, or GitHub Copilot
- • Experience with distributed training technologies such as DDP or FSDP
- • Knowledge of large language models (LLMs), generative AI, or AI agents
- • Experience with large-scale testing, developer tooling, or machine learning infrastructure
- • Exposure to cloud platforms such as AWS, Azure, or GCP
- • Experience with Docker, Kubernetes, CI/CD, or MLOps practices
- • Knowledge of Rust or TypeScript
- • Contributions to open-source projects, research publications, or personal technical projects
Benefits
- Remote (U.S.) work arrangement
Company Overview
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