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I’m a software engineer building low-latency AI/ML and distributed systems, with a focus on real-time market data, anomaly detection, and production-grade ML workflows. I enjoy turning complex pipelines into reliable, observable services—whether that’s optimizing feature generation at high throughput or integrating streaming components with robust backend interfaces. I also lead end-to-end delivery: containerizing models, setting up CI/CD, and deploying self-hosted LLM/AI infrastructure with RAG and secure inference flows. From engineering monitoring and alerting to designing APIs and dashboards for operational decision support, I aim to ship dependable systems that improve responsiveness, uptime, and measurable business outcomes.…I’m a software engineer building low-latency AI/ML and distributed systems, with a focus on real-time market data, anomaly detection, and production-grade ML workflows. I enjoy turning complex pipelines into reliable, observable services—whether that’s optimizing feature generation at high throughput or integrating streaming components with robust backend interfaces. I also lead end-to-end delivery: containerizing models, setting up CI/CD, and deploying self-hosted LLM/AI infrastructure with RAG and secure inference flows. From engineering monitoring and alerting to designing APIs and dashboards for operational decision support, I aim to ship dependable systems that improve responsiveness, uptime, and measurable business outcomes.

Kartik Malhotra

Software Engineer, AI Engineer, Data Scientist, +2

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I’m a software engineer building low-latency AI/ML and distributed systems, with a focus on real-time market data, anomaly detection, and production-grade ML workflows. I enjoy turning complex pipelines into reliable, observable services—whether that’s optimizing feature generation at high throughput or integrating streaming components with robust backend interfaces. I also lead end-to-end delivery: containerizing models, setting up CI/CD, and deploying self-hosted LLM/AI infrastructure with RAG and secure inference flows. From engineering monitoring and alerting to designing APIs and dashboards for operational decision support, I aim to ship dependable systems that improve responsiveness, uptime, and measurable business outcomes.…I’m a software engineer building low-latency AI/ML and distributed systems, with a focus on real-time market data, anomaly detection, and production-grade ML workflows. I enjoy turning complex pipelines into reliable, observable services—whether that’s optimizing feature generation at high throughput or integrating streaming components with robust backend interfaces. I also lead end-to-end delivery: containerizing models, setting up CI/CD, and deploying self-hosted LLM/AI infrastructure with RAG and secure inference flows. From engineering monitoring and alerting to designing APIs and dashboards for operational decision support, I aim to ship dependable systems that improve responsiveness, uptime, and measurable business outcomes.

Available to hire

I’m a software engineer building low-latency AI/ML and distributed systems, with a focus on real-time market data, anomaly detection, and production-grade ML workflows. I enjoy turning complex pipelines into reliable, observable services—whether that’s optimizing feature generation at high throughput or integrating streaming components with robust backend interfaces.

I also lead end-to-end delivery: containerizing models, setting up CI/CD, and deploying self-hosted LLM/AI infrastructure with RAG and secure inference flows. From engineering monitoring and alerting to designing APIs and dashboards for operational decision support, I aim to ship dependable systems that improve responsiveness, uptime, and measurable business outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Beginner

Language

English

Intermediate

Hindi

Intermediate

Work Experience

Software Engineer at Techonlogies LLP

July 1, 2024 - Present

Developed and maintained low-latency Python/C++ HFT pipelines for processing 1,000+ ticks/sec, enabling real-time market-data feature generation and predictive modeling to improve anomaly detection and trading-signal responsiveness. Designed high-throughput streaming workflows for market data and optimized backend components and feature-generation paths for real-time quantitative workloads. Built and operated self-hosted AI/ML infrastructure using Ollama, vLLM, Qwen3.5-Coder, and Llama 3.370B with RAG pipelines, integrating GitLab Duo CI for secure production ML/AI workflows. Integrated predictive and AI workflows into responsive React/TypeScript dashboards for real-time monitoring and operational decision support (sub-millisecond state-management performance target). Engineered a Datadog-style observability platform unifying metrics, alerting, and automated reporting, reducing MTTR by 40% and improving production visibility. Applied C++ libraries with socket and REST interfaces using

Software Engineer at Technologies LLP

July 1, 2024 - Present

Developed and maintained low-latency Python/C++ HFT pipelines processing 1,000+ ticks/sec, building real-time market data features and predictive modeling workflows to improve anomaly detection and trading-signal responsiveness. Designed high-throughput streaming data processing workflows for real-time quantitative workloads, optimizing backend components and feature-generation paths. Built and operated self-hosted AI/ML infrastructure using Ollama/vLLM with Qwen and LLaMA models with RAG pipelines and GitLab Duo integration for secure production ML/AI workflows. Integrated predictive and AI workflows into responsive React/TypeScript dashboards for real-time monitoring and operational decision support. Engineered a Datadog-style observability platform (metrics, alerting, automated reporting), reducing MTTR by ~40% and improving visibility. Implemented reusable internal C++ libraries with socket and REST interfaces and object-oriented abstractions for reliable communication. Applied pyt

Software Engineer at Softech Technologies LLP

July 1, 2024 - Present

Developed and maintained low-latency Python/C++ HFT pipelines processing 1,000+ ticks per second, building real-time market data features and predictive modeling workflows to improve anomaly detection and trading-signal responsiveness. Designed high-throughput streaming market data processing workflows, optimizing backend components and feature generation paths for real-time quantitative workloads. Built and operated self-hosted AI/ML infrastructure using Ollama, vLLM, Qwen 3.5-Coder and Llama 3.370B with RAG pipelines and GitLab Duo CI integration for secure production ML/AI workflows. Integrated predictive/AI workflows into responsive React/TypeScript dashboards for real-time monitoring and operational decision support, achieving sub-millisecond state-management performance. Engineered a Datadog-style production observability platform (metrics, alerting, automated reporting), reducing MTTR by 40% and improving production visibility. Applied pytest-based unit/integration testing and a

Remote Software Developer (AI/ML) at Poppler Reach

January 1, 2024 - March 1, 2024

Deployed a VA(D)ER-based NLP model for real-time sentiment analysis and topic extraction across 50,000+ monthly customer communications, reducing high-priority ticket response times from 4 hours to under 45 minutes. Containerized and deployed ML microservices using Docker for consistent CI/CD delivery and deployed an XGBoost churn prediction model that reduced customer attrition by 18%. Built AI/ML interfaces for enterprise integration using Pydantic validation and REST endpoints, improving structured model outputs and downstream reliability.

Remote Software Developer (AI/ML) at PopplER? each

January 1, 2024 - March 1, 2024

Deployed a VADER-based NLP model for real-time sentiment analysis and topic extraction across 50,000+ monthly customer communications, reducing high-priority ticket response time from 4 hours to under 45 minutes. Containerized and deployed ML microservices using Docker for consistent CI/CD delivery, and deployed an XGBoost churn prediction model that reduced customer attrition by 18%.

Remote AI/ML Software Developer at Poppler each

January 1, 2024 - March 1, 2024

Deployed a VADER-based NLP model for real-time sentiment analysis and topic extraction across 50,000+ monthly customer communications, reducing high-priority ticket response times from 4 hours to under 45 minutes. Containerized and deployed ML microservices with Docker for consistent CI/CD delivery, including an XGBoost churn prediction model that reduced customer attrition by 18%.