AI / Machine Learning Developer
<p><strong>Organimi</strong><span> (www.organimi.com) is a leading B2B SaaS software publisher, and we’re searching for an experienced </span><strong>AI / Machine Learning Developer.</strong></p><p><br></p><p><span>The successful candidate will be a key contributor to Organimi’s next generation of intelligent product features and automation systems focused on building, fine-tuning, and integrating AI models into our platform. You’ll develop, train, and deploy custom large language models (LLMs) and related machine learning systems tailored to our business domain, as well as build supporting microservices and APIs for seamless integration into our web and data stack.</span></p><p><br></p><p><span>You’ll also work on MCP (Model Context Protocol) servers, connectors, and middleware that interface our AI systems with our web applications and cloud infrastructure. This is an opportunity to join a small, highly collaborative team with big ambitions, where your contributions will have direct and visible impact.</span></p><p><br></p><p><span>Our ideal candidate will be based in the Greater Toronto Area (GTA) or Kitchener-Waterloo, where most of our team currently works from, but remote applicants across Canada are welcome. We’re looking for a self-starter who thrives in virtual team environments and wants to make a meaningful contribution to our AI innovation roadmap.</span></p><p><br></p><p><strong>Responsibilities: </strong></p><ul><li><span>Design, train, and fine-tune AI and machine learning models, including large language models (LLMs) and embedding models, to support domain-specific features within Organimi’s platform.</span></li></ul><p><span>Create and prepare high-quality training data from Organimi’s datasets for fine-tuning.</span></p><p><span>Apply feature engineering and parameter-efficient fine-tuning techniques (e.g., LoRA / QLoRA) to optimize model adaptation and performance.</span></p><ul><li><span>Develop and implement retrieval-augmented generation (RAG) pipelines that connect Organimi’s data to LLMs for real-time contextual responses.</span></li></ul><p><span>Handle data conversions (e.g., JSON → vector embeddings) and prompt-to-embedding mappings for semantic retrieval and knowledge lookups.</span></p><p><span>Integrate and maintain vector databases and related retrieval layers for scalable, context-aware AI interactions.</span></p><ul><li><span>Build MCP servers, RESTful APIs, and Python-based backend services to integrate AI capabilities into our existing applications and data systems.</span></li><li><span>Work with structured and unstructured datasets to develop AI features that enhance productivity, automation, and insight extraction.</span></li><li><span>Research, evaluate, and implement open-source LLM frameworks, vector databases, and model orchestration tools (e.g., LangChain, Ollama, Hugging Face, vLLM, etc.).</span></li><li><span>Collaborate with product and engineering teams to design and deliver intelligent features that align with customer needs.</span></li><li><span>Maintain and monitor model performance and accuracy through ongoing evaluation, retraining, and prompt optimization.</span></li><li><span>Participate in architecture reviews, code reviews, and agile sprints as part of our collaborative development process.</span></li><li><span>Assist in the creation of tools, dashboards, and monitoring systems for model operations (MLOps).</span></li></ul><p><br></p><p><strong>What you’ll bring: </strong></p><ul><li><span>Degree or diploma in Computer Science, Data Science, Software Engineering, or a related technical field.</span></li><li><span>1–3 years of professional experience in AI/ML software development or a related field.</span></li><li><span>Proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, FastAPI, or scikit-learn.</span></li><li><span>Ability to design and implement custom neural network models using Organimi’s data, beyond traditional LLM fine-tuning, to address specific automation or prediction tasks.</span></li><li><span>Direct experience with LLM development and fine-tuning, including data preparation, tokenization, and model serving.</span></li><li><span>Understanding of MCP (Model Context Protocol) and experience building or connecting to MCP-compatible servers or clients.</span></li><li><span>Familiarity with vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS) and embedding models.</span></li><li><span>Solid understanding of microservices, APIs, and cloud architectures (AWS, Azure, or Google Cloud).</span></li><li><span>Experience integrating AI services with front-end applications or SaaS platforms.</span></li><li><span>Strong communication and organizational skills with the ability to work independently in a distributed team.</span></li><li><span>Proficiency with Git, issue tracking, and agile collaboration tools.</span></li></ul><p><br></p><p><strong>Nice to have but not required: </strong></p><ul><li><span>Experience developing or deploying custom AI agents or chatbot systems.</span></li><li><span>Familiarity with LangChain, OpenAI API, Anthropic Claude, or similar LLM ecosystems.</span></li><li><span>Experience with prompt engineering, RAG systems, and knowledge graph integration.</span></li><li><span>Experience with containerization (Docker) and CI/CD pipelines for AI workloads.</span></li><li><span>Prior experience developing for a SaaS platform or in the HRTech / B2B software space.</span></li><li><span>Experience contributing to open-source ML projects or publishing technical AI content.</span></li><li><span>Familiarity with MLOps tools such as MLflow, Kubeflow, or SageMaker, and with AWS Bedrock and related cloud-based AI/MLOps services.</span></li></ul><p><strong> </strong></p><p><strong>To Apply:</strong></p><ul><li><span>Attach your current Resume. Cover Letter optional </span></li><li><span>Include links to relevant work samples — such as GitHub repos, model cards, Hugging Face profiles, or AI demos.</span></li><li><span>Optional: describe a model or AI system you’ve built or fine-tuned that you’re particularly proud of.</span></li></ul><p><br></p><p><br></p><p><strong>Note: This is a remote position as part of a virtual team, with members clustered around Toronto and Kitchener-Waterloo. The successful candidate will telecommute and participate with all other team members in a weekly online company meeting and other online team meetings as scheduled. Our team typically works Monday to Friday from 9am to 5pm but like all software companies we are “always on” when customers need us. While we appreciate interest from all applicants, we will be contacting only those applicants selected for interviews. </strong></p><p><br></p>