About the job :

Introduction :

About Us

- SymphonyAI is a leading enterprise AI solutions provider helping retailers and manufacturers optimize business operations through advanced analytics, planning, and automation solutions.

- Our products support global organizations in improving supply chain efficiency, inventory performance, forecasting accuracy, and customer satisfaction.

- We are committed to delivering measurable outcomes for our clients through innovative technology, deep domain expertise, and strong customer partnerships.

Job Description

Job Summary

- Shelf Intelligence is our core retail execution product, providing automated in-store shelf audits at scale for CPG and retail customers.

- Accuracy, consistency, and measurable improvement over time depend on strong feedback loops between production data and the AI/CV models behind the pipeline.

- The CV team develops and improves a retail shelf recognition pipeline spanning detection, product recognition, OCR, and spatial / planogram analysis.

- This pipeline generates a large volume of scan data, model behavior signals, and RCA outputs.

- This role focuses on turning that data into stronger evaluation, clearer failure analysis, better performance reporting, and targeted experiment support.

About The Role

- Build , train & maintain CV Data Science Models and frameworks across detection, recognition, and OCR, with strong statistical rigor in benchmark design and result interpretation

- Work closely with Global Data Science Team , Engineering team and Implementation teams for Model testing , deployment abd accuracy testings .

- Mine scan meta-reports, model behavior logs, and RCA outputs to identify systematic failure modes and improvement opportunities

- Partner with CV engineers on targeted analyses and experiments, including retrieval evaluation, post-processing analysis, and planogram / compliance-related error analysis

- Build SQL-based analytics, dashboards, and recurring reports to make model performance observable across releases

- Support dataset engineering workflows, including data quality analysis, gap analysis, hard-case mining, and benchmark set curation

About You

- ML proficiency in Computer Vision & Deep learning with hands-on exposure to image / CV problems such as classification, detection, embeddings, or OCR

- Strong Python proficiency, including pandas, numpy, scikit-learn, PyTorch ,TensorFlow ,OpenCV

- Strong SQL and relational database fundamentals, with experience working directly on large datasets using joins, aggregations, window functions, and query optimization

- Strong grounding in statistics, including hypothesis testing, sampling, confidence intervals, and experiment design

Good to have

- Retail / CPG domain familiarity

- Experience with dashboarding and observability tools such as Grafana

- Experience with evaluation tooling or experiment tracking platforms such as MLflow or Weights & Biases

- Exposure to large-scale production ML systems and MLOps practices

- Experience communicating analytical findings to technical and non-technical stakeholders

- Familiarity with cloud data platforms (AWS, GCP, or Azure)

About Us :

What We Offer :

- Competitive salary and benefits package.

- Opportunity to work on high-impact retail forecasting and supply chain programs.

- Exposure to leading global retailers and advanced AI-driven planning solutions.

- A collaborative and fast-paced work environment.

- Learning and growth opportunities across retail, supply chain, and data science domains