Senior Applied AI Engineer turning machine learning research into production features for Clariti’s government technology platform. Building LLM, computer vision, and agentic AI capabilities.
Responsibilities
Serve as a forward-deployed AI expert across Clariti's product teams
Turn machine learning research into production-ready features spanning LLMs, agentic AI workflows, computer vision, and multimodal learning
Own computer vision and agentic AI problem domains
Select and adapt architectures and training/fine-tuning strategies
Design and execute experiments end to end
Evaluate model performance and determine which approaches to pursue
Identify high-impact opportunities to improve AI systems
Make trade-offs across model accuracy, interpretability, latency, and cost
Share experience with research teammates and improve experimental rigor
Stay current on techniques, benchmarks, and tooling across computer vision, generative AI, NLP, and multimodal learning
Embed with product teams and partner with product and engineering managers
Scope problems, build proofs of concept, and take solutions through production using MLOps tooling and infrastructure
Bring proposed approaches to the CivCheck AI Research team for design feedback
Report into the CivCheck AI Research team while working day to day with product and engineering managers
Requirements
7–10 years of hands-on experience in applied AI/ML in industry
Track record of shipping models and systems that solved real business problems
Experience as the lead or sole AI expert on a project, taking work from proof of concept through production
Fluency with MLOps practices and infrastructure, including CI/CD for models, containerization, deployment, and monitoring
Ability to operate independently inside cross-functional teams
Experience building agentic AI workflows and LLM-powered applications in production, including retrieval, tool use, evaluation, and guardrails
Experience training and fine-tuning models using modern frameworks
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
Experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworks
Experience with end-to-end ML workflows on AWS, Azure, or GCP
Software engineering skills including Git, testing, API design, and modular code
Experimental and statistical intuition
Excellent communication skills
Successful candidates must undergo comprehensive background checks
Candidates must be able to participate in occasional travel for in-person meetings
Bonus: experience in forward-deployed, embedded, or solutions engineering roles
Bonus: experience developing high-accuracy computer vision systems under strict tolerances
Bonus: exposure to construction, building, civic-tech, or regulatory/compliance domains
Benefits
Competitive compensation packages
Time off
Benefits to keep you and your family healthy
Occasional travel for in-person company-wide or departmental meetings, typically 1–2 times per year
Accommodations and support during the application, interview, testing, and hiring process
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