About the Role:
Our R&D team builds cutting-edge visual intelligence for the global retail industry, analyzing complex in-store scenes and dense shelf environments across major markets worldwide. We combine deep learning, modern Vision-Language Models (VLMs), and generative AI to extract real-time understanding from retail imagery at massive scale.
Recently, we expanded into Augmented Reality (AR) - merging machine learning, 2D/3D geometry, and computer graphics to deliver interactive, spatial experiences directly onto edge devices. As an AI Researcher on this team, you will focus on solving non-trivial algorithmic challenges, developing visual and multimodal architectures, and shipping production-grade solutions deployed across thousands of stores globally.
About FORMFORM powers the world’s two billion mobile workers as they change companies and industries for good, with mobile technology that improves execution from the frontline. FORM solutions include the AI-enabled task management platform GoSpotCheck, Trax’s image recognition technology, and FORM OpX, all of which activate and connect teams in the field – with leaders, missions, and each other – so they can deliver success in the enterprise. With more than 25 years of experience, FORM supports 100,000+ global users from some of the world’s more recognizable global brands in 45 countries.
RequirementsKey Responsibilities:
- Model Development & Optimization: Train, fine-tune, and evaluate deep learning models and Vision-Language Models (VLMs) tailored for fine-grained retail scene understanding and product recognition.
- AR & Spatial Solutions: Design and implement features bridging computer vision and computer graphics, applying 2D/3D geometric principles to power interactive Augmented Reality workflows.
- Edge & On-Device Deployment: Profile, optimize, and quantize non-trivial algorithms for latency- and memory-constrained edge hardware (e.g., mobile devices and embedded systems).
- VLM & Generative AI Innovation: Work hands-on with multimodal LLMs, VLMs, and advanced prompting techniques to create next-generation automated recognition tools.
- Algorithm Refinement & Scaling: Enhance and optimize existing algorithms to ensure high efficiency, robustness against varying store conditions, and global scalability.
- Benchmarking & Rigorous Evaluation: Systematically benchmark, test, and evaluate ML models against real-world retail datasets to ensure top-tier accuracy and reliability.
Requirements & Qualifications:
- Experience: 3+ years of hands-on experience developing and deploying Machine Learning and Deep Learning models in production or applied R&D environments.
- Computer Vision & Math Foundations: Strong understanding of classical and modern computer vision, along with the linear algebra, calculus, and mathematical foundations required for 2D/3D geometry and spatial graphics.
- Multimodal & Generative AI: Practical experience working with modern LLMs/VLMs and prompt engineering techniques.
- Core Tech Stack: High proficiency in Python and deep learning frameworks (Keras, Tensorflow, Jax preferred).
- Research-to-Product Mindset: Strong problem-solving ability to take complex academic/R&D concepts and adapt them into robust, non-trivial production features.
- Communication: Comfortable collaborating daily in English, both written and verbal, in a distributed international team.
Nice to Have:
- Experience with Augmented Reality frameworks (e.g., ARKit, ARCore) or computer graphics pipelines (OpenGL, WebGL, or game engines).
- Edge Computing: Familiarity with optimizing models for edge devices and inference runtimes (e.g., CoreML, or TFLite).
- Prior domain experience in retail analytics, planogram compliance, or fine-grained object recognition.
What We Offer:
- Full remote or hybrid work from our cozy office in Krakow.
- The option to enroll in a medical package on preferential terms.
- Subsidized English language courses.
- Company-provided work equipment.
- Opportunities for internal growth and career development.
- Access to internal learning resources.
Compensation: 25,000 - 35,000 PLN per month. Exact compensation may vary depending on skills, experience, and location within Poland.
Skills Required
- 3+ years of hands-on experience developing and deploying machine learning and deep learning models in production or applied R&D environments
- Strong understanding of classical and modern computer vision
- Strong linear algebra, calculus, and mathematical foundations for 2D/3D geometry and spatial graphics
- Practical experience with modern LLMs, VLMs, and prompt engineering techniques
- High proficiency in Python
- Experience with deep learning frameworks such as Keras, TensorFlow, or JAX
- Strong problem-solving ability to adapt academic or R&D concepts into production features
- Comfortable collaborating in English, both written and verbal, in a distributed international team
- Experience with augmented reality frameworks such as ARKit or ARCore
- Experience with computer graphics pipelines such as OpenGL, WebGL, or game engines
- Familiarity with optimizing models for edge devices and inference runtimes such as Core ML or TensorFlow Lite
- Experience in retail analytics, planogram compliance, or fine-grained object recognition
What We Do
Powered by leading technology and proprietary data, Trax connects brands, retailers, and shoppers, setting the standard for retail excellence. Trax's AI-powered platform uniquely combines solutions that provide unparalleled data-driven signals to leading global CPGs and retailers to deliver real-time data, retail execution, and consumer engagement to increase ROI. 30 of the world's top 50 CPG companies, along with leading retailers and emerging brands, use Trax's shelf monitoring, analytics, merchandising, activation, and shopper engagement solutions at scale to drive positive shopper experiences and unlock revenue opportunities at all points of sale. Trax is a global company with hubs in the United States, Singapore, France, Hungary, China, Mexico, Japan, Brazil, and Israel, serving customers in more than 80 countries worldwide. To learn more, visit traxretail.com..
