About the role
Company: IG DefenceLocation: NoidaEmployment Type: Full-Time
MissionIG Defence builds autonomous, intelligent defence systems designed to operate in real, adversarial environments—not demos, not simulations.As an AI/ML Software Engineer, you will build production-grade machine learning systems that power perception, prediction, decision-making, and autonomy across defence platforms.This role is for engineers who want to own outcomes, deploy to real systems, and solve problems where failure is not an option.What You’ll DoBuild and ship machine learning systems used in live defence platformsDesign, train, and deploy models for:Classification, detection, and predictionTime-series and sensor data modelingAnomaly detection and decision supportOwn the end-to-end ML lifecycle:Data pipelines → model training → evaluation → deployment → monitoringOptimize models for real-world constraints:LatencyCompute limitsReliability under degraded conditionsWrite production-quality software, not notebooksIntegrate ML outputs into autonomy, control, and command systemsWork directly with systems, hardware, and field teamsIterate based on field performance, not academic metrics
What You’ll Build ForAutonomous and semi-autonomous defence systemsEdge-deployed AI pipelinesDecision-support and threat-assessment systemsSensor-driven intelligence platformsMission-critical software stacks
What We’re Looking ForRequiredStrong proficiency in PythonSolid software engineering fundamentals:Data structuresAlgorithmsSystem designHands-on experience with machine learning frameworks:PyTorch and/or TensorFlowExperience building and deploying real ML systems, not just modelsAbility to reason about failure modes, edge cases, and reliabilityComfort working in Linux-based production environmentsPreferredExperience with:Model optimization and deployment (ONNX, TensorRT, etc.)Time-series, sensor fusion, or streaming dataDistributed or edge ML systemsExposure to robotics, autonomy, aerospace, or defence domainsFamiliarity with:CI/CD for MLModel monitoring and performance driftExperience working with restricted datasets or secure systems
How You’ll Be EvaluatedCan you design ML systems that survive real-world conditions?Can you turn ambiguous problems into shipped software?Can you debug systems where ML meets hardware and physics?Can you take ownership and deliver without constant oversight?
Why This Role MattersYour work will run on operational systems, not presentationsYour models will influence real decisions, not benchmarksYour code will be tested by reality, not test casesYou will see direct impact—from development to deployment
GrowthEngineer → Senior EngineerSenior → Technical LeadLead → Principal / Systems ArchitectGrowth is based on impact, ownership, and execution—not titles.