ML Engineer

Reposted 7 Days Ago
Hiring Remotely in USA
Remote
78-78 Hourly
Senior level
HR Tech • Other • Professional Services
The Role
The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.
Summary Generated by Built In
Machine Learning Engineer (LLM Fine-Tuning) | Remote


Location: Fully Remote
Contract Rate: Up to USD78/hour

About our Client

Our client helps business leaders make better strategic decisions through in-depth expert interviews and curated insights. Our mission is to transform the way executives access and apply real-world expertise.

We’re a small, highly technical, and product-focused team working to leverage AI to scale human expertise.

About the Role

We’re seeking a Machine Learning Engineer experienced in fine-tuning and deploying Large Language Models (LLMs). You’ll work closely with our product and data teams to build, refine, and operationalize intelligent systems that enhance how our users interact with expert insights.

This is a hands-on engineering role, ideal for someone who’s comfortable working autonomously and thrives in a fast-moving environment.

Responsibilities
  • Design, fine-tune, and deploy LLMs for natural language understanding, text generation, and summarization tasks.

  • Optimize existing ML models for performance, cost, and latency.

  • Build and maintain robust data pipelines for model training and evaluation.

  • Collaborate with cross-functional teams to integrate AI-driven features into production systems.

  • Continuously explore new techniques in prompt engineering, retrieval-augmented generation (RAG), and model optimization.

Requirements
  • Proven experience fine-tuning and deploying LLMs (OpenAI, Anthropic, Mistral, LLaMA, etc.).

  • Strong background in machine learning engineering, with experience in Python and frameworks such as PyTorch, TensorFlow, or Transformers.

  • Solid understanding of NLP, model evaluation, and data preprocessing.

  • Experience building end-to-end ML systems, from data ingestion to deployment.

  • Familiarity with MLOps tools and cloud infrastructure (AWS, GCP, or Azure).

  • Excellent communication and documentation skills.

Nice to Have
  • Experience working with vector databases (Pinecone, Weaviate, FAISS).

  • Understanding of RAG, prompt tuning, or instruction fine-tuning.

  • Previous work in content intelligence, research, or knowledge management platforms.

Why Join
  • Work directly with a lean, high-impact team passionate about AI and product quality.

  • Fully remote and flexible working schedule.

  • Opportunity to influence the AI roadmap of a company transforming access to human expertise.

Top Skills

AWS
Azure
GCP
Python
PyTorch
TensorFlow
Transformers
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The Company
HQ: Delray Beach, Florida
201 Employees
Year Founded: 2016

What We Do

G2i is a hiring community connecting remote developers with world-class engineering teams. Our unique approach combines rigorous technical assessments with a solid commitment to developer health, ensuring companies get skilled developers who are supported, valued, and ready to execute from day one.

Our transparent vetting process includes in-depth, performance-ranked developer profiles, recorded technical interviews, and soft-skills assessments. Whether you're working on a short-term project or burning down a backlog, G2i connects you with a community of pre-vetted developers.

Planning to hire ten or more engineers? We create a Custom Talent Pipeline, allowing for specific customizations in sourcing, assessment criteria, technical interview questions, and integration with your existing HR systems and processes.

G2i partners with clients who support the developer health mission—matching developers with environments that improve their health, support recovery from burnout, and enable professional growth through restful work.

Is your team overworked or understaffed? Contact us today to learn how G2i can help you.

More information about our mission and commitment to developers and clients can be found at https://g2i.co or follow us on X @g2i_co

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