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Machine Learning Engineer, Remote

Machine Learning Engineer, Remote

JobgetherUS
12 days ago
Job type
  • Full-time
  • Remote
  • Quick Apply
Job description

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.

Requirements

  • 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.
  • Benefits

  • Competitive compensation package with potential for bonus.
  • Core benefits including medical, dental, vision, and 401(k) matching.
  • Flexible remote, hybrid, or in-office work arrangements.
  • Generous paid time off, including vacation, sick leave, holidays, and volunteer time.
  • Professional development and career growth opportunities.
  • Wellness initiatives supporting mental and physical health.
  • Inclusive, collaborative, and award-winning work culture.
  • Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

    When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

    🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

    📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.

    🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

    🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

    The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

    Thank you for your interest!

    #LI-CL1

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