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Machine Learning Engineer (LLM Fine-Tuning) | Remote
Location
: Fully RemoteContract Rate: Up to USD78/hourAbout our ClientOur 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 RoleWe’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. ResponsibilitiesDesign, 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 HaveExperience 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.
Location
: Fully RemoteContract Rate: Up to USD78/hourAbout our ClientOur 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 RoleWe’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. ResponsibilitiesDesign, 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 HaveExperience 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.
The company
G
G2i Remote
