AI/ML Engineer

About us:

Bajaj Broking is building modern, cloud-native platforms that power trading, lending, and wealth at scale. Our tech teams work in fast-moving, real-time environments, shipping production-ready ML and AI systems with a sharp focus on performance, reliability, and secure-by-design engineering.

Role Overview:

We are looking for Senior ML & AI Ops Engineer to design and operationalize end-to-end ML and AI systems across hybrid cloud environments. This role focuses on traditional ML/DL models and AI workloads and ensures scalable, secure, and compliant deployment. You will build CI/CD pipelines for ML models, automate training workflows, manage model registries, monitor drift, and integrate AIOps for predictive infrastructure scaling.

What You’ll Do

Own ML Ops at Scale

• Design and ship end-to-end ML CI/CD pipelines—from training and validation to production rollout and safe rollbacks.
• Build feature stores and model registries that ensure reproducibility, traceability, and fast experimentation.
• Automate data pipelines for structured and unstructured data, powering reliable model training.
• Enable rapid experimentation using MLflow / W&B, including hyperparameter tuning and experiment tracking.
• Scale distributed training on GPU clusters, optimizing performance and resource usage.

Build AI Ops–First Infrastructure

• Run production ML/AI workloads on Kubernetes with autoscaling and GPU orchestration.
• Create repeatable, cloud-native environments using Terraform and Helm.
• Integrate AIOps platforms to drive predictive scaling, anomaly detection, and smarter operations.

Make Systems Observable & Resilient

• Build rich observability dashboards for model accuracy, latency, throughput, and drift.
• Implement proactive alerting and incident response for pipelines and model failures.
• Define and maintain SLOs/SLAs, keeping ML services highly available and production-ready.

Engineer for Security & Compliance

• Embed Zero Trust, RBAC, secrets management, and encryption by design.
• Ensure ML systems meet SEBI/RBI, GDPR, and internal data governance standards.
• Maintain full auditability for model approvals and deployments.

Optimize for Speed & Cost

• Maximize GPU utilization across training and inference workloads.
• Drive cloud cost efficiency through batching, quantization, caching, and smart autoscaling.

What You Bring

• Strong Python engineering and hands-on experience with CI/CD (GitHub Actions, GitLab CI, Azure DevOps).
• Deep experience across the ML lifecycle using MLflow, Kubeflow, Airflow, W&B.
• Production-grade expertise in Docker and Kubernetes.
• Infrastructure as Code using Terraform and Helm.
• Observability stack experience: Prometheus, Grafana, OpenTelemetry.
• Working knowledge of data pipelines and platforms (Spark, Kafka, S3 / Blob).

Bonus Points If You’ve Worked On

• Financial ML use cases like risk, fraud, or forecasting.
• AIOps and predictive infra scaling.
• GPU optimization and model acceleration using ONNX, TensorRT.

Bajaj Broking

• Work on production AI systems at scale in a highly visible, business-critical environment.
• Be part of a team that values engineering depth, ownership, and innovation.
• Opportunity to influence the AI platform strategy of a leading financial services brand.
• Competitive compensation, strong leadership support, and a culture that encourages learning and experimentation.

Bajaj Broking is an equal opportunity employer. We are committed to building an inclusive workplace where diverse perspectives help us create better technology and better outcomes for our customers.