ML Engineer, Generative AI & Computer Vision

About Skandor Technologies

Skandor Technologies builds production-ready AI products that help enterprises modernize workflows, improve decision-making, and create operational leverage. We focus on generative AI, automation, data platforms, and supply-chain intelligence to support end-to-end digital transformation. We work with clients from product strategy and validation through to delivery of scalable enterprise platforms. Our teams collaborate closely with industry partners, solving complex technical and business problems using advanced AI and software engineering, in an environment that emphasizes innovation, reliability, and real-world impact for enterprise customers.

The Role

You'll work on a live, production generative-AI platform that turns a plain-language brief or reference image into a manufacturable 3D model and a priced bill of materials. The work spans multimodal LLMs, image generation, 3D geometry, and computer vision, and your results feed directly into customer quotes. That makes accuracy, evaluation, and reliability part of the job.

What You'll Do

• Build and improve multimodal AI pipelines: structured extraction, tool/function calling, retrieval over curated knowledge bases, and image generation and editing
• Improve output fidelity using conditioning techniques (e.g., ControlNet-style or geometry-guided generation) and prompt/parameter strategies
• Develop computer-vision and 3D components: mesh processing, rendering, object counting, and scale/weight estimation
• Design evaluation and QA workflows to measure accuracy and catch regressions
• Add confidence checks and human-in-the-loop review where model outputs affect pricing
• Ship ML services with FastAPI on AWS, and manage model versions, fallbacks, latency, and API cost
• Use AI coding tools to move faster, and review what they produce criticallyRequired Skills
• Bachelor's degree in Computer Science, Engineering, or a related field
• Strong Python, including async programming and REST API development (FastAPI)
• Hands-on experience with LLM/multimodal APIs (Gemini, OpenAI, Claude, or similar): prompt engineering, structured JSON outputs, tool/function calling
• Understanding of RAG and knowledge-base grounding
• Computer vision fundamentals (OpenCV, image processing) and familiarity with generative image models (diffusion, ControlNet-style conditioning)
• Experience evaluating ML/LLM outputs (metrics, test sets, error analysis)
• Working knowledge of AWS (S3, ECS/Fargate, RDS) or an equivalent cloud
• SQL/PostgreSQL, Git, Docker, and testing with pytest
• Comfort using AI-assisted development tools in daily work
• Clear written and verbal communication, and the ability to explain model behavior to non-technical stakeholders
• Adaptability: you pick up new models, tools, and APIs quicklyGood to Have
• 3D/mesh processing (trimesh, Open3D, pyrender) or geometry/graphics background
• PyTorch or TensorFlow, and model fine-tuning experience
• Observability and cost monitoring for AI workloads, and CI/CD or Infrastructure-as-Code (CDK/Terraform)
• Data-labeling or QA tooling experienceWho You Are

A curious engineer who likes making AI reliable in production, not just impressive in a demo, and who can work directly with clients and teammates.