Senior Applied AI Engineer

We're seeking a Senior Applied AI Engineer to serve as a forward-deployed AI expert across Clariti's product teams. You'll turn the latest machine learning research into practical, production-ready features, spanning large language models (LLMs), agentic AI workflows, computer vision, and multimodal learning. You'll report into our CivCheck AI Research team, while your day-to-day work will be embedded with product and engineering managers across the company.

Responsibilities

Drive projects end to end: scoping the problem, building the proof of concept, and taking it to production with MLOps tooling and infrastructure; Own computer vision and agentic AI problem domains, selecting and adapting architectures and training/fine-tuning strategies for complex, unstructured real-world data; Drive the design and execution of experiments end to end, from framing the question to evaluating model performance; Help shape technical direction by identifying high-impact opportunities to improve AI systems; Make pragmatic trade-off calls across model accuracy, interpretability, latency, and cost, and own decisions in communication with stakeholders; Share experience with research teammates and help raise the bar for experimental rigor; Stay current on techniques, benchmarks, and tooling across computer vision, generative AI, NLP, and multimodal learning; Embed with product teams across Clariti to identify where AI can create the most value for customers

Requirements

7–10 years of hands-on experience in applied AI/ML in industry, with a track record of shipping models and systems that solved real business problems; Demonstrated experience as the lead or sole AI expert on a project, taking your own work from proof of concept through to production without relying on a dedicated ML engineering team; Hands-on fluency with MLOps practices and infrastructure, including CI/CD for models, containerization, deployment, and monitoring; A proven ability to operate independently inside cross-functional teams, working closely with product managers, engineering managers, and nontechnical stakeholders; Strong experience building agentic AI workflows and LLM-powered applications in production, including retrieval, tool use, evaluation, and guardrails; Deep, demonstrated experience training and fine-tuning models using modern frameworks, including defining architectures, curating and cleaning datasets, tuning training parameters, and diagnosing training and validation performance; Significant experience with computer vision and image processing, including feature extraction, object detection, segmentation, and geometric transformations; Familiarity with diffusion models, model distillation, or multimodal architectures in production; Strong proficiency in Python and experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworks; Hands-on experience with end-to-end ML workflows on cloud platforms such as AWS, Azure, or GCP; Strong software engineering skills, including Git, testing, API design, and modular code that non-ML engineers can maintain; Sharp experimental and statistical intuition; Excellent communication skills, able to align stakeholders, justify trade-offs, write clear design proposals, and explain AI concepts to engineers, executives, and customers

Nice to have

Experience in a forward-deployed, embedded, or solutions engineering role, bringing AI into teams or products that didn't have it before; Experience developing computer vision systems requiring high accuracy and reliability under strict tolerances, for example in autonomous vehicles, medical imaging, or industrial inspection; Preference for or comfort thriving in an early-stage or startup environment; Interest in the ethical implications of AI technology and responsible AI development and design; Exposure to the construction, building, civic-tech, or regulatory/compliance domains

Benefits

Competitive compensation packages; Time off; Benefits for you and your family (depending on employment type)