We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Machine Learning Engineer, Remote at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Machine Learning Engineer. in the . United States. .. This role focuses on designing, developing, and deploying advanced machine learning solutions that leverage large language models (LLMs) to enhance intelligent automation, analytics, and client engagement. You will work with cross-functional teams to architect agentic workflows, optimize prompt engineering strategies, and integrate state-of-the-art LLMs. The position provides the opportunity to contribute to cutting-edge ML products while applying DevOps best practices and maintaining scalable, secure infrastructure. The environment encourages experimentation, collaboration, and innovation, with a focus on delivering high-impact solutions for global users. This is a fully remote role, allowing flexibility while collaborating with technical teams across multiple time zones.. Accountabilities:. Architect agentic workflows enabling multi-agent orchestration for intelligent automation features.. Design, implement, and refine prompts and analytics feedback systems for large language models.. Integrate and evaluate LLMs such as GPT-4, GPT-5, Claude, and LLaMA for use cases including coding assistance, analytics insights, and data tutoring.. Collaborate with engineering teams to ensure latency-optimized solutions and smooth onboarding of multiple models.. Maintain deployment pipelines, implement automated testing, and ensure code quality through reviews and CI/CD processes.. Contribute to documentation, release planning, and beta testing processes, including sandbox integrations.. Ensure security, compliance, and observability for ML functions and libraries.. Bachelor’s degree in Computer Science, Machine Learning, or a related field.. 3+ years of experience in machine learning engineering or backend development using Python (3.8–3.12).. Hands-on experience with LLM integration, prompt engineering, and agentic frameworks (e.g., OpenAI Responses API, LangChain).. Familiarity with RESTful APIs, microservices, AWS, Docker, and Kubernetes.. Understanding of DevOps best practices including infrastructure as code, observability, and security.. Knowledge of RBAC, audit logging, and version control for ML functions and libraries.. Strong problem-solving, critical thinking, and collaboration skills.. Company Location: United States.