Top Python Developer Jobs in Delhi

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Internship role to develop and deploy user-growth algorithms: user segmentation, recommendations, LTV/churn/conversion models, A/B testing, causal inference analyses, and collaborate with product and engineering to drive measurable growth.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Design and build batch and real-time data ingestion pipelines, ETL/ELT solutions, data lakes and warehouses. Develop and optimize data models and microservices using Spring Boot. Ensure data quality, governance, security, observability, CI/CD, and cloud-native deployment on Azure/AKS. Collaborate across teams and support operational monitoring and performance optimization.

Build and own Firework's go-to-market systems and data infrastructure to generate enterprise leads end-to-end. Design CRM architecture, enrichment, scoring, routing, and automated outbound/inbound flows. Partner with Sales to define qualified leads, use AI tooling to prototype lead-gen automations, and continuously test and iterate to grow a qualified pipeline.

Own end-to-end quality validation for new features and releases on a genomics platform. Design, build, and maintain scalable automated regression suites (Playwright/Cypress/Selenium), run API/integration tests (Postman/Swagger), integrate tests into CI/CD, lead exploratory testing and release readiness, track defects to resolution, improve QA processes, and mentor junior QA engineers while communicating quality risks across teams.

Remote internship supporting recruiter data operations: clean and analyze data, maintain website hosting and data structures, build API calls and automation scripts, perform web scraping, and communicate findings to stakeholders.

Lead SRE responsibilities for reliability, scalability, performance, monitoring, automation, disaster recovery, DR drills, chaos testing, capacity planning, security best practices, and documentation while collaborating with development and business teams.

Design, build, and scale cloud-native Python backend services and data-backed applications. Develop RESTful APIs, microservices, and asynchronous event-driven systems. Deploy and operate production workloads on Kubernetes and at least one public cloud (AWS or Azure). Work with cloud data warehouses (Snowflake or Databricks) and relational databases, ensuring scalable, reliable distributed systems.

Build and maintain scalable backend services for an AI legal product: fine-tune LLMs, create data processing and document/OCR pipelines, integrate LLMs, and manage infrastructure with Terraform/OpenTofu and Docker.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, build, and maintain scalable backend services and microservices using Go and Python; develop REST/gRPC APIs; integrate databases and cloud services; write tests, perform code reviews, debug production issues, and collaborate cross-functionally.

Build and maintain scalable ETL pipelines on GCP, transform large/disconnected datasets, automate and optimize data delivery, support stakeholders, and apply data engineering best practices including testing and release management.

Design, train, and productionize state-of-the-art object detection systems. Build robust training pipelines, perform error analysis and ablations, optimize inference for latency and memory, and deliver production services with Docker, CI/CD, and APIs. Implement testing, monitoring, model versioning, and retraining pipelines. Rapidly prototype research ideas into deployable components and maintain clear technical documentation.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

Design, build, and optimize scalable data pipelines and models using Spark, Kafka, Airflow, dbt, and SQL across GCP and AWS. Ingest and normalize marketing and analytics data, ensure data quality and governance, support analytics and reporting, and collaborate with cross-functional global teams.

Design, implement, and manage Azure DevOps CI/CD pipelines and repositories; automate infrastructure provisioning (ARM/Bicep/Terraform); manage Azure services (App Services, Functions, Storage, Key Vault); deploy and lifecycle-manage Power Platform solutions (Power Apps, Power Automate, Power BI) using ALM practices; script in PowerShell/Bash/Python; monitor, troubleshoot, and optimize deployments while collaborating with stakeholders.

Lead solution and enterprise architecture for .NET-based systems. Design cloud-native AWS/Azure solutions, microservices, serverless patterns, and RESTful APIs. Oversee databases, DevOps/containerization (Docker/Kubernetes), integration tools, security and regulatory compliance (FedRAMP, HIPAA, FDA), and mentor engineering teams while driving adoption of modern tooling and CI/CD practices.

Design, implement, and maintain scalable AWS infrastructure and CI/CD pipelines. Automate provisioning (Terraform/CloudFormation/Ansible), manage containers (Docker/EKS), ensure monitoring, security, cost optimization, and disaster recovery, and collaborate with development and QA for reliable deployments.

Lead end-to-end analytics and ML for growth: LTV, retention, segmentation, attribution, and predictive models. Partner with Paid Media, Product, and Engineering to build production-ready ML pipelines, inform SEM and bidding, monitor product metrics, and present actionable insights to stakeholders.