Machine Learning Engineer III
CommerceIQ (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 35–55 LPA
Posted 1h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and maintain multiple AI-driven end-to-end machine learning pipelines for B2B SaaS products, including components with Human-in-the-Loop to improve quality.
- Own the ML infrastructure roadmap collaborating with Data Science and platform teams to enable scaling, deployment, and performance monitoring of large-scale machine learning models.
- Build tools and capabilities supporting the entire ML lifecycle: data ingestion, feature engineering, model development, and deployment, including cutting-edge algorithms like LLMs on GPU and distributed computing.
Minimum Requirements
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or Statistics from a reputed college.
- 7+ years of experience in machine learning engineering including deploying large scale ML models to production in batch and real-time environments.
- Experience with distributed computing frameworks (e.g., Spark, Map-Reduce), cloud platforms (AWS/GCP/Azure), and infrastructure-as-code tools like Terraform.
- Strong programming proficiency in Python and SQL; experience with ML frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, pandas, NumPy.
Ideal Candidate Profile
- Experienced in architecting and building AI pipelines supporting productionization of ML models at scale within fast-growing SaaS environments.
- Demonstrated ability to lead ML infrastructure projects end-to-end, from research experiments to deployment and scaling.
- Familiarity with handling large datasets, optimizing ML workflows, and driving cross-functional collaborations to deliver impactful AI-driven solutions for Fortune 100 retail customers.