AI & ML Engineer
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AI & ML Engineer
Location
US
Experience
Senior
Posted
Jul 7, 2026
Apply by
August 6, 2026
Applicants
0
Early applicantFull-timeWork from Home
Job Description
**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.
**How Jobgether works:**
We use an **AI-powered matching process** to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
[Why Apply Through Jobgether?](https://jobgether.com/how-jobgether-works)
**Data Privacy Notice:** By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
Key Responsibilities
- Design, develop, deploy, and maintain production-grade AI and machine learning systems.
- Collaborate with backend, frontend, and platform engineering teams to integrate AI capabilities.
- Build, deploy, and optimize LLM-powered applications for quality, latency, and reliability.
- Own end-to-end development of RAG pipelines, intelligent agents, and workflow automation.
- Design and execute evaluation, testing, monitoring, and validation processes for AI models.
- Implement software engineering best practices including CI/CD, version control, and deployment strategies.
- Partner with cross-functional stakeholders to deliver scalable AI-driven solutions.
Requirements
- Bachelor's degree in Computer Science
- Engineering
- Mathematics
- or a related technical field
Skills Required
PythonMachine LearningLarge Language ModelsLLM-based systemsCloud infrastructureSystems designSoftware testingPerformance optimizationScalable application architectureAnalytical skillsCommunicationProblem-solvingAbility to explain complex technical conceptsAbility to work independentlyCollaborationLangChainLlamaIndexHugging FaceMLflowWeights & BiasesDVCDistributed systems
Benefits
- Competitive compensation package
- Remote-friendly work environment
- Flexibility
- Professional growth opportunities
- Collaborative engineering culture
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