Senior Software Engineer - Machine Learning
New
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LegionArtificial Intelligence
Remote USAFull-TimeSenior
Salary230,000 - 270,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- Backend DevelopmentPythonKubernetesMachine LearningRustRESTful APIsLLMDistributed Systems
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- 5+ years of experience building production software systems.
- Strong software engineering skills with experience in Rust, Python, or similar programming languages.
- Proven ability to build scalable backend services, distributed systems, APIs, or data-intensive applications.
- Hands-on experience integrating large language models or other foundation models into production applications.
- Ability to design, evaluate, and improve AI systems through experimentation, quantitative evaluation, and continuous iteration.
- Familiarity with modern AI engineering patterns such as structured outputs, tool calling, context engineering, multimodal systems, or AI workflows.
- Strong understanding of software engineering best practices, including testing, observability, reliability, and maintainability.
- Demonstrated ability to take ownership of technically ambiguous projects from design through production.
- Excellent communication and collaboration skills with the ability to work effectively across cross-functional teams.
- Growth mindset and low ego, with a willingness to learn, adapt, and collaborate.
Responsibilities
- Design, build, and maintain the core AI capabilities that power intelligent experiences across the platform.
- Develop reusable capabilities for model integration, reasoning, multimodal understanding, structured generation, evaluation, and other foundational AI functionality.
- Optimize the AI systems that power these capabilities through experimentation, quantitative evaluation, context engineering, and iterative refinement.
- Apply your production software engineering experience to build backend services, APIs, and distributed AI systems.
- Partner closely with cross-functional partners to deploy scalable AI services that enable product teams to rapidly build AI-powered experiences.
- Rapidly prototype emerging AI techniques and translate successful experiments into production-ready platform capabilities.
- Support production systems by debugging failures and continuously improving latency, reliability, observability, and operational performance.
- Stay current with advances in AI engineering, foundation models, and applied machine learning, applying them where they create meaningful customer value.
- Optimize AI systems for performance, latency, reliability, scalability, and cost.
- Contribute to a collaborative engineering culture focused on ownership and continuous learning.
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