This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI & ML Engineer based in the United States.
Join an innovative engineering team building enterprise-grade AI solutions that deliver measurable business impact. In this role, you'll develop and operate production-ready AI and machine learning systems that power intelligent workflows at scale. Working closely with cross-functional engineering teams, you'll transform complex product requirements into reliable, high-performance AI capabilities. This position offers the opportunity to work with cutting-edge large language models, retrieval systems, and cloud-native technologies while applying strong software engineering principles. If you're passionate about bringing AI into real-world production environments and solving meaningful technical challenges, this is an excellent opportunity to shape the future of enterprise AI.
Accountabilities:
- Design, develop, deploy, and maintain production-grade AI and machine learning systems that support enterprise-scale products.
- Collaborate with backend, frontend, and platform engineering teams to integrate AI capabilities into robust, scalable application workflows.
- Build, deploy, and continuously optimize LLM-powered applications, balancing quality, latency, reliability, and operational costs.
- Own the end-to-end development of retrieval-augmented generation (RAG) pipelines, intelligent agents, and workflow automation systems.
- Design and execute rigorous evaluation, testing, monitoring, and validation processes for AI models in both offline and production environments.
- Continuously improve model performance through experimentation, tuning, and system-level optimizations.
- Implement software engineering best practices for AI development, including testing, CI/CD, version control, deployment strategies, and rollback procedures.
- Stay informed on advancements in applied AI and generative technologies, translating emerging techniques into practical product enhancements.
- Partner with cross-functional stakeholders to understand business objectives and deliver scalable AI-driven solutions.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
- 5+ years of professional experience across software engineering and applied AI or machine learning development.
- Strong proficiency in Python and experience building production-quality software applications.
- Proven experience deploying, operating, and maintaining ML or LLM-based systems in production environments.
- Solid understanding of machine learning fundamentals, model evaluation methodologies, and engineering trade-offs.
- Experience deploying AI systems using cloud infrastructure and modern software development practices.
- Strong background in systems design, software testing, performance optimization, and scalable application architecture.
- Excellent analytical, communication, and problem-solving skills with the ability to explain complex technical concepts clearly.
- Ability to work independently while collaborating effectively within a senior engineering team.
- Experience with frameworks such as LangChain, LlamaIndex, or Hugging Face is highly desirable.
- Familiarity with RAG architectures, ML lifecycle tools (such as MLflow, Weights & Biases, or DVC), distributed systems, or enterprise environments is considered an advantage.
Benefits
- Competitive compensation package.
- Remote-friendly work environment with flexibility.
- Opportunity to own and shape critical production AI systems with significant business impact.
- Work alongside experienced engineers on cutting-edge AI, machine learning, and large language model technologies.
- Exposure to enterprise-scale products operating in real-world production environments.
- Collaborative engineering culture focused on innovation, quality, and continuous learning.
- Opportunity for professional growth while contributing to the future of enterprise AI.
- Modern engineering practices with a production-first approach to AI development.