CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week.
Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.
Technical Expertise
- Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
- Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
- Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
- Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
- Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
- Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
- Applied Problem-Solving
Mandatory skill -
- Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
- Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
- Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.
Leadership & Collaboration
- Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
- Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
- Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.
Other
- Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
- Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.
Education & Experience
- Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
- 7+ years of hands-on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.
Skills Required
- Strong background in machine learning, deep learning, and NLP with experience training/fine-tuning large-scale models (LLMs, transformers, diffusion models)
- Demonstrated success adapting foundation models to domain-specific applications via fine-tuning or transfer learning
- Hands-on expertise with Parameter-Efficient Fine-Tuning (LoRA, prefix tuning, adapters) and quantization-aware training
- Proficiency in PyTorch, TensorFlow, and the Hugging Face ecosystem
- Experience with distributed training frameworks (DeepSpeed, PyTorch Lightning, Ray)
- Basic understanding of MLOps best practices: experiment tracking, model versioning, CI/CD for ML pipelines, production deployment
- Experience working with large datasets, feature engineering, and data pipelines (Spark, Databricks, or cloud-native ML services)
- Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML)
- Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC
- Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization
- Experience in applied AI across NLP, computer vision, multimodal systems, or related domains
- Proven ability to lead and mentor applied scientists and ML engineers; 2+ years in a leadership/managerial role
- 7+ years hands-on experience in applied machine learning and data science
- Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or related field
- Strong cross-functional collaboration and excellent communication/presentation skills for technical and non-technical audiences
- Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques
What We Do
CommerceIQ is the leader in E-commerce Channel Optimization (ECO), the practice of using machine learning, analytics and automations to optimize the e-commerce channel across supply chain, marketing and sales operations to win at the moment of purchase and drive profitable market share growth.
Why Work With Us
CommerceIQ is building innovative products in a hot market, in a pre-IPO company with a bold vision, and with passionate colleagues who are collectively building a company for the long run. We have developed a culture to support our growth and deliver a unique employee experience with market competitive pay and exceptional benefits.
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