AI Software Engineer – Systems
| Company | Nexus |
|---|---|
| Location | San Francisco, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Mid Level, Senior |
Requirements
- 3+ years of hands-on software development experience, with a focus on building and scaling backend systems (bonus if some of that is with AI or data-intensive applications)
- Strong coding skills in Python, C++, or similar languages, and solid computer science fundamentals (data structures, algorithms, etc.)
- Experience with AI/ML: Familiarity with machine learning frameworks (e.g. PyTorch, TensorFlow) and a good understanding of how ML models work
- Cloud & DevOps savvy: Experience deploying applications on cloud platforms (AWS, GCP, etc.) and using containers/orchestration (Docker, Kubernetes) to build scalable systems
- Problem-solving chops: Excellent debugging and problem-solving skills – you enjoy digging into complex systems to figure out how things work (and how to make them better)
- Adaptability: Comfortable working in a fast-paced, agile environment. You pick up new technologies quickly and aren’t afraid of the unknown
- Team player attitude: Great communication skills and a collaborative spirit. You enjoy working with others and sharing knowledge in a supportive, no-ego team
- Education: Bachelor’s degree in Computer Science or related field (or equivalent practical experience)
Responsibilities
- Design & build the core systems and services that power our AI products, ensuring they are scalable, secure, and highly performant
- Develop and optimize machine learning pipelines (from data ingestion to training and real-time inference) to deliver AI features quickly and reliably
- Integrate new machine learning models into production applications, working closely with ML engineers to turn prototypes into rock-solid services
- Monitor and improve system performance and reliability in production – you’ll debug issues, tweak performance, and ensure our infrastructure can grow with our user base
- Collaborate with a small, cross-functional team (ML engineers, data scientists, product managers) to brainstorm ideas, plan projects, and rapidly ship new features
- Rapidly prototype new ideas and experiments to push the boundaries of our AI capabilities – we love quick iterations and learning by doing
- Maintain quality: Write clean, maintainable code with proper tests, and participate in code reviews to keep our codebase top-notch
Preferred Qualifications
- Deep learning extras: Experience with GPU programming (CUDA) or optimizing model inference (we’ll be impressed if you can squeeze out extra speed from our models!)
- MLOps tools: Familiarity with tools like Kubeflow, MLflow, or other MLOps/DevOps pipelines to automate and streamline ML workflows
- Open-source contributions: You’ve contributed to open-source AI projects or have cool personal projects in AI/ML that you’re proud to share
- Ever-curious mindset: You stay up-to-date with the latest AI research and love tinkering with new models and technologies just for fun