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Customer Facing Applied AI Engineer, Retail Perception
Simbe
5 hours ago
Full-time
On-site
San Francisco, California, United States
Simbe is building the AI powered operating system for physical retail. Our autonomous robots and multimodal computer vision platform turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and customer focused product design to help retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity.
Simbe is looking for a Customer Facing Applied AI Engineer to help turn our computer vision and data platform into customer value across new and existing retail deployments. This role sits at the intersection of Computer Vision, Data, Product, Customer Success, and Field Operations. You will configure, tune, validate, and troubleshoot Simbe's AI pipelines for customer environments, helping retailers get accurate and actionable insights from Tally as quickly and reliably as possible.
Why This Role Is High Impact
You will be close to the customer and close to the technology, with direct influence on customer outcomes
You will translate real world deployment issues into repeatable product, pipeline, and model improvements
You will help Simbe scale across diverse store formats, fixture types, product categories, and retailer operating models
Responsibilities
Lead customer specific AI configuration. Configure and tune Simbe's computer vision and data pipelines for new customers, new store formats, and expanded robot deployments
Improve customer accuracy. Investigate and resolve issues related to out of stocks, price tags, promo tags, top stock, product association, fixture detection, shelf coverage, and data quality
Support launches and expansions. Partner with Sales, Implementation, Product, Customer Success, Data, Computer Vision, and Field teams to ensure new deployments meet customer requirements and scale smoothly
Own release validation. Test customer facing model and pipeline updates, evaluate accuracy impacts, and help manage deployment readiness for releases tied to customer needs
Analyze production data. Use Python, pandas, SQL, internal tools, logs, robot imagery, and customer outputs to diagnose problems, quantify impact, and recommend fixes
Build operational tooling. Create or improve internal tools that reduce deployment time, automate QA, expose data quality issues, and help customer facing teams move faster
Close the loop with Product and Engineering. Turn repeated customer issues into clear product requirements, engineering tickets, and model improvement opportunities
Required Qualifications
3+ years of experience in software engineering, applied machine learning, data engineering, computer vision operations, customer solutions engineering, or a related technical role
Strong Python skills and comfort working with data using pandas, notebooks, SQL, spreadsheets, or similar tools
Ability to troubleshoot complex technical issues across data pipelines, configurations, model outputs, logs, and customer reports
Comfort with Linux, command line workflows, Git, and production debugging
Strong analytical judgment, attention to detail, and ownership of customer outcomes
Ability to communicate clearly with technical and non technical stakeholders, including customer facing teams
Ability to prioritize effectively in a fast moving environment with evolving customer needs
Bonus Qualifications
Experience with computer vision, machine learning evaluation, model training, annotation workflows, or neural network outputs
Experience in retail technology, robotics, IoT, data products, enterprise SaaS, or customer implementation roles
Experience with dashboards, internal web tools, data validation, QA automation, or release management
Experience working directly with customer success, implementation, product, or sales teams
Familiarity with image data, OCR, object detection, product matching, or sensor driven systems
Simbe Values:
Result Driven - We are customer centric and results driven. We strive to create immense value for our team, partners, customers, and investors
Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally
Transparent - We value open communication internally, and with our partners and customers. We are receptive to feedback
Agile - We are eager to learn and adapt quickly to changes and customer needs
Innovative - We are bold and innovative, with an intense focus on product design, user experience, and customer value
Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
The base salary offered is based on market location and may vary depending on individualized factors for job candidates, including job related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include equity compensation, in addition to a full range of medical, financial, and other benefits. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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Simbe is looking for a Customer Facing Applied AI Engineer to help turn our computer vision and data platform into customer value across new and existing retail deployments. This role sits at the intersection of Computer Vision, Data, Product, Customer Success, and Field Operations. You will configure, tune, validate, and troubleshoot Simbe's AI pipelines for customer environments, helping retailers get accurate and actionable insights from Tally as quickly and reliably as possible.
Why This Role Is High Impact
You will be close to the customer and close to the technology, with direct influence on customer outcomes
You will translate real world deployment issues into repeatable product, pipeline, and model improvements
You will help Simbe scale across diverse store formats, fixture types, product categories, and retailer operating models
Responsibilities
Lead customer specific AI configuration. Configure and tune Simbe's computer vision and data pipelines for new customers, new store formats, and expanded robot deployments
Improve customer accuracy. Investigate and resolve issues related to out of stocks, price tags, promo tags, top stock, product association, fixture detection, shelf coverage, and data quality
Support launches and expansions. Partner with Sales, Implementation, Product, Customer Success, Data, Computer Vision, and Field teams to ensure new deployments meet customer requirements and scale smoothly
Own release validation. Test customer facing model and pipeline updates, evaluate accuracy impacts, and help manage deployment readiness for releases tied to customer needs
Analyze production data. Use Python, pandas, SQL, internal tools, logs, robot imagery, and customer outputs to diagnose problems, quantify impact, and recommend fixes
Build operational tooling. Create or improve internal tools that reduce deployment time, automate QA, expose data quality issues, and help customer facing teams move faster
Close the loop with Product and Engineering. Turn repeated customer issues into clear product requirements, engineering tickets, and model improvement opportunities
Required Qualifications
3+ years of experience in software engineering, applied machine learning, data engineering, computer vision operations, customer solutions engineering, or a related technical role
Strong Python skills and comfort working with data using pandas, notebooks, SQL, spreadsheets, or similar tools
Ability to troubleshoot complex technical issues across data pipelines, configurations, model outputs, logs, and customer reports
Comfort with Linux, command line workflows, Git, and production debugging
Strong analytical judgment, attention to detail, and ownership of customer outcomes
Ability to communicate clearly with technical and non technical stakeholders, including customer facing teams
Ability to prioritize effectively in a fast moving environment with evolving customer needs
Bonus Qualifications
Experience with computer vision, machine learning evaluation, model training, annotation workflows, or neural network outputs
Experience in retail technology, robotics, IoT, data products, enterprise SaaS, or customer implementation roles
Experience with dashboards, internal web tools, data validation, QA automation, or release management
Experience working directly with customer success, implementation, product, or sales teams
Familiarity with image data, OCR, object detection, product matching, or sensor driven systems
Simbe Values:
Result Driven - We are customer centric and results driven. We strive to create immense value for our team, partners, customers, and investors
Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally
Transparent - We value open communication internally, and with our partners and customers. We are receptive to feedback
Agile - We are eager to learn and adapt quickly to changes and customer needs
Innovative - We are bold and innovative, with an intense focus on product design, user experience, and customer value
Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
The base salary offered is based on market location and may vary depending on individualized factors for job candidates, including job related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include equity compensation, in addition to a full range of medical, financial, and other benefits. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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