AI Engineer – Freelancer

Twine; Canada; Remote; CAD 90,000 - 120,000; Full time

Job summary

A leading freelance marketplace in Canada is seeking an experienced AI Engineer to optimize and scale its AI-powered influencer marketing platform. You will enhance data pipelines for performance and cost-efficiency while tuning models and improving semantic search. Ideal candidates have strong Python skills and expertise in AWS serverless architecture, with a proven track record in AI/ML workflows. Join us to push the boundaries of automated insights and recommendations.

Qualifications

• Proven experience optimizing AI/ML pipelines, particularly image and embedding workflows.
• Strong proficiency in Python and AWS serverless architecture.
• Hands-on expertise with multi-modal embeddings and semantic search.

Responsibilities

• Take ownership of the existing AI data pipeline, focusing on performance and cost optimization.
• Optimize image-to-text and embeddings pipelines for speed, efficiency, and recall quality.
• Implement and improve batching, caching, concurrency, and queuing in a serverless AWS environment.

Skills

Optimizing AI/ML pipelines

Python proficiency

AWS serverless architecture

Multi-modal embeddings expertise

Semantic search familiarity

Experience with vector databases

LangChain knowledge

Problem-solving skills

Communication skills

Tools

AWS

Pinecone

OpenSearch

RunPod

Replicate

Job description

Join to apply for the AI Engineer – Freelancer role at Twine.

Join a project focused on advancing an AI‑powered influencer marketing platform by optimizing and scaling its data pipeline. The primary objective is to enhance the performance, cost‑efficiency, and recall quality of image‑to‑text and embeddings workflows. You will be responsible for refining batching, caching, concurrency, and queuing within a serverless AWS environment, as well as tuning models such as InternVL and Qwen using RunPod and Replicate. The role also involves improving semantic recall and retrieval quality for influencer content leveraging Pinecone and OpenSearch, and exploring multi‑modal embeddings to boost search accuracy. There is potential to expand the system into Retrieval‑Augmented Generation (RAG) and agentic AI workflows for automated insights and recommendations.

Responsibilities

• Take ownership of the existing AI data pipeline, focusing on performance and cost optimization.
• Optimize image‑to‑text and embeddings pipelines for speed, efficiency, and recall quality.
• Implement and improve batching, caching, concurrency, and queuing in a serverless AWS environment.
• Tune and deploy models (e.g., InternVL, Qwen) via RunPod and Replicate.
• Enhance semantic recall and retrieval quality using Pinecone and OpenSearch.
• Experiment with multi‑modal embeddings for improved search accuracy.
• Contribute to the development of RAG and agentic AI workflows for automated insights and recommendations.

Skills and Requirements

• Proven experience optimizing AI/ML pipelines, particularly image and embedding workflows.
• Strong proficiency in Python and AWS serverless architecture.
• Hands‑on expertise with multi‑modal embeddings and semantic search.
• Familiarity with vector databases (e.g., Pinecone, OpenSearch).
• Experience with LangChain, RAG, and related frameworks.
• Ability to work independently and deliver robust, scalable solutions.
• Excellent problem‑solving and communication skills.

About Twine

Twine is a leading freelance marketplace connecting top freelancers, consultants, and contractors with companies needing creative and tech expertise. Trusted by Fortune 500 companies and innovative startups alike, Twine enables companies to scale their teams globally.

Our Mission

Twine's mission is to empower creators and businesses to thrive in an AI‑driven, freelance‑first world.