Join Our Team

Job Description:

As an AI Engineer at Smart Terminal, you will lead the integration of Small Language Models (SLMs) and complex reasoning engines directly into the Bash environment. You will be responsible for pushing the boundaries of local, offline AI performance, ensuring millisecond-level inference latency while maintaining strict memory constraints.

Key Responsibilities:

• Architect and deploy quantized local AI models (Llama, LLaVA, Mistral).
• Optimize inference engines using ONNX Runtime, TensorRT, or llama.cpp.
• Develop secure, sandboxed execution environments for AI-generated Bash scripts.
• Collaborate on RAG pipelines using local vector databases for offline documentation search.

Experience Requirements:

• 3+ years of professional experience in Machine Learning or AI Engineering.
• Deep understanding of LLM architectures, fine-tuning, and quantization techniques.
• Expertise in Python, PyTorch, and deep familiarity with Linux/Bash internals.
• (Bonus) Experience with Rust or C++ for high-performance systems programming.

Job Description:

As our primary Data Scientist, you will dive deep into anonymized usage data and developer workflow patterns. You will design rigorous experiments, build predictive heuristics, and analyze complex interactions to systematically improve Smart Terminal's command generation accuracy and contextual awareness.

Key Responsibilities:

• Design and analyze A/B tests to measure the impact of new LLM prompts on user success rates.
• Build and maintain dashboards tracking model hallucination rates, latency, and retention.
• Develop unsupervised models to cluster user behaviors and discover high-friction CLI tasks.
• Collaborate closely with AI Engineers to identify data blind-spots for model fine-tuning.

Experience Requirements:

• 2+ years of industry experience in Data Science or Product Analytics.
• Strong foundation in statistical analysis, hypothesis testing, and causal inference.
• Proficiency in Python (Pandas, Scikit-learn, Jupyter) and advanced SQL.
• Strong product sense with the ability to translate technical metrics into user-centric product decisions.

Job Description:

Data Engineers at Smart Terminal are responsible for the lifeblood of our operation: the training data. You will architect exabyte-scale ETL pipelines that continuously scrape, clean, deduplicate, and format vast troves of Linux documentation, man pages, and bash scripts to feed our model training procedures.

Key Responsibilities:

• Design and deploy scalable, fault-tolerant data pipelines using orchestration tools (Airflow/Prefect).
• Build distributed web scraping systems to aggregate technical documentation across the web.
• Implement data quality checks, sanitization pipelines, and schema enforcement for unstructured text.
• Optimize vector database infrastructure for fast retrieval in RAG integrations.

Experience Requirements:

• 3+ years of backend or data engineering experience in high-volume environments.
• Expertise in Python, Go, or Java, alongside strong command of SQL and NoSQL architectures.
• Experience with big data processing frameworks (Spark, Hadoop, or Ray).
• Familiarity with cloud infrastructure (AWS/GCP), Docker, and container orchestration (Kubernetes).

Job Description:

We are looking for highly motivated, curious, and passionate interns who want hands-on experience building the future of open-source AI developer tools. You will not be fetching coffee; you will be writing code, testing SLMs (Small Language Models), and contributing directly to the core Smart Terminal codebase under the mentorship of our senior engineers.

Key Responsibilities:

• Assist in developing and integrating new features into the Smart Terminal bash environment.
• Run benchmarks and performance tests on various local AI models (Llama, Qwen, etc.).
• Help improve our documentation, setup scripts, and automated testing pipelines.
• Research and prototype new developer workflows using the latest LLM APIs.

Experience Requirements:

• Currently pursuing or recently completed a degree in Computer Science, Software Engineering, or a related field.
• Strong foundational knowledge of Python and comfortable navigating a Linux terminal.
• A genuine passion for open-source software, AI, and building tools for developers.
• Willingness to learn fast, ask questions, and tackle complex problems head-on.