Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I’m a Senior AI/ML Engineer with over 10 years of experience building production-grade machine learning and distributed systems. My work focuses on large language models, retrieval-augmented generation (RAG), GPU-accelerated training, and scalable inference platforms deployed on cloud-native infrastructure. I’ve led end-to-end AI system design — from model development and fine-tuning to deployment, monitoring, and reliability engineering. I’m passionate about building AI systems that are not just innovative, but measurable, reliable, and impactful in real-world environments.…I’m a Senior AI/ML Engineer with over 10 years of experience building production-grade machine learning and distributed systems. My work focuses on large language models, retrieval-augmented generation (RAG), GPU-accelerated training, and scalable inference platforms deployed on cloud-native infrastructure. I’ve led end-to-end AI system design — from model development and fine-tuning to deployment, monitoring, and reliability engineering. I’m passionate about building AI systems that are not just innovative, but measurable, reliable, and impactful in real-world environments.

Satinder Pal Singh

Full Stack Developer, Back-End Developer, Web Developer, +5





I’m a Senior AI/ML Engineer with over 10 years of experience building production-grade machine learning and distributed systems. My work focuses on large language models, retrieval-augmented generation (RAG), GPU-accelerated training, and scalable inference platforms deployed on cloud-native infrastructure. I’ve led end-to-end AI system design — from model development and fine-tuning to deployment, monitoring, and reliability engineering. I’m passionate about building AI systems that are not just innovative, but measurable, reliable, and impactful in real-world environments.…I’m a Senior AI/ML Engineer with over 10 years of experience building production-grade machine learning and distributed systems. My work focuses on large language models, retrieval-augmented generation (RAG), GPU-accelerated training, and scalable inference platforms deployed on cloud-native infrastructure. I’ve led end-to-end AI system design — from model development and fine-tuning to deployment, monitoring, and reliability engineering. I’m passionate about building AI systems that are not just innovative, but measurable, reliable, and impactful in real-world environments.

Available to hire

I’m a Senior AI/ML Engineer with over 10 years of experience building production-grade machine learning and distributed systems. My work focuses on large language models, retrieval-augmented generation (RAG), GPU-accelerated training, and scalable inference platforms deployed on cloud-native infrastructure. I’ve led end-to-end AI system design — from model development and fine-tuning to deployment, monitoring, and reliability engineering. I’m passionate about building AI systems that are not just innovative, but measurable, reliable, and impactful in real-world environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

Javanese

Fluent

Work Experience

Senior Software Engineer at Deep Knowledge Group

November 1, 2021 - Present

End-to-end backend platform modernization spanning microservices, event-driven architecture, and observability for a high-traffic data intelligence platform. Architected scalable Spring Boot microservices with DDD, implemented Kafka-based asynchronous workflows to decouple services and improve resilience. Designed distributed caching with Redis and optimized database indexing, reducing latency on read-heavy endpoints. Improved CI/CD pipelines using Docker and Jenkins, accelerating releases and enabling multiple production deployments per week. Introduced structured logging, distributed tracing, and observability tooling with CloudWatch and the ELK stack, improving incident resolution speed. Modeled core domain aggregates (DataAsset, Pipeline, IngestionJob) using DDD, and built event-driven data ingestion pipelines processing millions of records daily with Kafka Streams and schema registry. Implemented Saga orchestration for multi-service data enrichment workflows; built DLQs, circuit b

Senior Software Engineer at DeepSync (Deep Sync One)

January 1, 2019 - October 1, 2021

Led backend engineering for a high-scale audience data marketplace enabling activation of 200,000+ audience segments across LiveRamp and Oracle Data Cloud ecosystems. Designed event-driven ingestion pipelines using Kafka with guaranteed delivery semantics; built microservices for audience segmentation, data enrichment, and marketplace integrations using Spring Boot and Spring Cloud. Implemented CQRS-based read/write separation to optimize activation workflows under high traffic; strengthened platform security with JWT-based authentication and GDPR-aligned data controls. Reduced reporting latency and improved activation speed by 35% through asynchronous processing and Redis caching. Modeled aggregates AudienceSegment, DataProvider, ActivationRequest; architected a schema-evolution strategy using Avro and Confluent Schema Registry to maintain backward compatibility across 40+ Kafka topics. Implemented idempotent consumers and transactional outbox for exactly-once processing. Built GraphQ

Full Stack Developer at NetSuite (Oracle NetSuite – #1 AI Cloud ERP)

January 1, 2017 - January 1, 2019

Contributed to AI-powered Cloud ERP platform modernization for enterprise customers across 40+ countries. Developed backend services handling financial transactions, order management, and reporting pipelines for high-volume enterprise workloads. Implemented event-driven financial processing workflows using asynchronous messaging patterns with JMS and Kafka for reliability and fault tolerance. Optimized database performance for high-volume ERP transactions using Oracle SQL tuning. Built secure REST APIs supporting accounting, billing, and compliance-driven modules with strict RBAC. Modeled core ERP entities (Invoice, PurchaseOrder, JournalEntry, VendorPayment) using JPA/Hibernate; designed a batch processing framework with Spring Batch for nightly reconciliation of 500,000+ transactions. Built reusable UI components for dashboards; multi-currency and multi-subsidiary support; automated regression testing with JUnit 5 and Mockito; embedded SOX, GAAP, IFRS validation rules into API middle

Senior AI/ML Engineer at Deep Knowledge Group

November 1, 2021 - Present

AI/ML platform engineering for a high-traffic data intelligence platform, delivering production-ready predictive models, GenAI infrastructure, NLP pipelines, and scalable microservices. Led design of deep learning models trained on large-scale signals, improved early identification and classification accuracy by 32% across platform data streams; built a complete RAG pipeline with LangChain, LlamaIndex, FAISS, and prompt chaining; implemented hallucination mitigation and confidence-based routing, achieving substantial reductions in hallucination rates. Optimized GPU utilization on NVIDIA A100/H100 clusters with mixed-precision training, gradient checkpointing, and DeepSpeed ZeRO, reducing training time and cost. Deployed Triton Inference Server with dynamic batching and model ensembles; accelerated inference latency with TensorRT/ONNX Runtime; implemented end-to-end CI/CD and observability tooling. Architected event-driven data ingestion with Kafka, and built scalable Spring Boot micros

Senior AI/ML Engineer at DeepSync (Deep Sync One)

January 1, 2019 - October 1, 2021

NLP pipelines, vector search, and GPU-accelerated inference for an audience data marketplace. Designed and fine-tuned BERT/RoBERTa/DistilBERT for classification, NER, and semantic matching; built hybrid vector search with FAISS, BM25, and sentence-transformers; accelerated embedding generation on CUDA-enabled GPUs. Implemented Kafka-based ingestion and CQRS-based read/write separation to support high-traffic model-serving workloads; developed microservices with Spring Boot; automated training/evaluation/deployment with Azure ML/MLflow; containerized pipelines with Docker/Kubernetes and Helm; ensured backward-compatible schema evolution with Avro/Confluent; introduced OpenTelemetry instrumentation and end-to-end observability.

ML Engineer & Full Stack Developer at NetSuite (Oracle NetSuite)

January 1, 2017 - January 1, 2019

Cloud ERP platform modernization with ML integrations for predictive analytics, anomaly detection, and automation. Built anomaly detection models (Isolation Forests, autoencoders) reducing false positives in fraud detection; developed predictive analytics pipelines for financial forecasting; designed real-time streaming pipelines with Kafka for ML feature inputs; authored custom NLP pipelines for compliance/document processing; implemented batch processing with Spring Batch and performance tuning for high-volume ERP workloads; ensured security/compliance with JWT-based RBAC and SOX/GAAP/IFRS validation rules; improved CI/CD with Jenkins and automated regression testing; enabled multi-currency/subsidiary support and reliable deployments.