Company DescriptionProjectMark is an all-in-one CRM and proposal platform built specifically for the construction industry. We provide companies with all the tools necessary to win the next job – industry specific pipeline & contact management, a digital asset library for proposal integrationRole Description
We’re looking for an AI/ML Engineer to build the next generation ofAI tooling on top of our CRM platform at ProjectMark. You’ll play a critical role in designing intelligent agents and workflows that enhance how construction professionals manage their work, relationships, and data. From intelligent opportunity scoring to auto-completing forms and surfacing insights, you’ll help us bring powerful, purpose-built AI into our customers' daily experience.We are seeking a highly motivated candidate who is enthusiastic about diving into new challenges. The ideal candidate will have a strong work ethic, be ready to invest the necessary hours, and be fully dedicated to contributing to the success of the team. If you're passionate about solving meaningful problems and eager to make an impact, we warmly invite you to join us at ProjectMark. Your drive and commitment will be valued and celebrated as we build something extraordinary together.Responsibilities
Design, develop, and deploy machine learning models—both LLMs and smaller task-specific models—to power intelligent features within the ProjectMark CRM
Build agentic workflows that automate internal tasks and enhance user productivity through contextual decision-making
Fine-tune, train, and evaluate models on proprietary datasets, applying methods like LoRA, PEFT, or instruction tuning where appropriate
Architect retrieval-augmented systems (RAG) using vector databases and embedding models for dynamic context injection
Implement intelligent agents using prompt chaining, memory systems, and external tool integrations
Collaborate cross-functionally with Product, Engineering, and Customer Success to uncover impactful AI use cases across the platform
Continuously monitor, evaluate, and optimize model performance using telemetry and user feedback
Ensure scalability, security, and reliability of deployed ML systems within our broader infrastructure
Stay current with advancements in machine learning, agent frameworks, and model training techniques—bringing fresh ideas into production
Contribute to the long-term AI roadmap, helping shape strategy while driving hands-on implementationRequirements
8+ years in backend/software engineering and 3+ years of applied machine learning experience
Proven experience training and fine-tuning machine learning models, not limited to LLMs
Strong grasp of ML fundamentals: supervised/unsupervised learning, model selection, overfitting/underfitting, metrics, etc.
Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
Experience working with domain-specific datasets to train or adapt models to unique contexts
Familiarity with transformer-based models, embeddings, and techniques like LoRA, PEFT, and instruction tuning
Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and embedding pipelines
Knowledge of agentic design principles, including autonomous/multi-agent workflows and tool use
Ability to build and maintain robust ML infrastructure (e.g., training pipelines, evaluation loops, inference services)
Bonus: Exposure to MLOps, model deployment, or building internal tooling for AI/ML teams