Full Stack ML Engineer

Location: Bangalore, India

Experience: 0–2 years

Employment Type: Full-time

About Spurring Ventures

Spurring Ventures is an AI-first startup delivering production-ready AI/ML solutions that combine innovation with enterprise-grade reliability. Our solutions are built on Azure AI Foundry, Hugging Face, MLflow, and Kubernetes, and deployed across GPU/TPU/CPU clusters. We are a lean, high-performance team, and we're looking for multi-skilled engineers who can contribute across the entire AI/ML lifecycle — from model development to production support.

Role Overview

As a Junior Full Stack ML Engineer, you will work on end-to-end AI/ML product development. This includes designing and training models, developing APIs and dashboards, deploying solutions on Azure, and maintaining/monitoring systems in production. This is a hands-on role where you will create, test, deploy, and support real-world AI products from Day 1.

Key Responsibilities

· Develop and fine-tune ML models using PyTorch, TensorFlow, Hugging Face.

· Build APIs (FastAPI) and dashboards (React/Next.js) to deliver AI solutions.

· Containerize workloads using Docker and deploy on Azure Kubernetes Service (AKS).

· Automate CI/CD pipelines with GitHub Actions + Azure DevOps.

· Manage model versioning and experiment tracking with MLflow.

· Write and maintain unit, integration, and validation tests.

· Monitor production systems with Azure Monitor, Prometheus, Grafana.

· Provide L1/L2 post-production support to clients, including troubleshooting and incident resolution.

· Ensure compliance with AI governance, audit, and risk management standards.

Required Qualifications

· Bachelor's/Master's degree in Computer Science, Data Science, AI/ML, or related field.

· 0–2 years of experience (internships/projects in ML or cloud deployments considered).

· Strong programming in Python (ML + backend); familiarity with JavaScript/React a plus.

· Knowledge of ML frameworks (PyTorch, TensorFlow, Scikit-learn).

· Understanding of cloud deployments (preferably Azure).

· Familiarity with Git, Docker, CI/CD pipelines.

· Strong problem-solving and debugging skills.

Required Certifications (at least one, more is a plus)

· Microsoft Certified: Azure AI Engineer Associate (AI-102)

· Microsoft Certified: Azure Data Scientist Associate (DP-100)

· Microsoft Certified: Azure Fundamentals (AZ-900)

· Microsoft Certified: DevOps Engineer Expert (AZ-400) (bonus for CI/CD focus)

· TensorFlow Developer Certificate (for ML competency)

Preferred Certifications (good-to-have, not mandatory)

· AWS Certified Machine Learning – Specialty (demonstrates cross-cloud ML knowledge)

· Certified Kubernetes Application Developer (CKAD) (for containerization & AKS)

Why Join Us

· Work on live client projects from Day 1.

· Exposure to Azure AI, Hugging Face, MLflow, and Kubernetes.

· Mentorship from senior architects & AI leaders.

· Lean team = high ownership, rapid learning, and fast career growth.

· Competitive salary + performance incentives.

· Career path to Full Stack ML Engineer Tech Lead AI Architect.