Top Python Developer Jobs in Delhi

Specialist responsible for Ab Initio Metadata Hub administration, metadata scripting, data lineage, ETL processes, SQL and stored procedures. The role investigates root causes, resolves complex issues, retrieves backend metadata, and supports end-to-end data landscapes spanning source systems, warehouses, marts, and reporting. Candidates should have strong Ab Initio expertise, communication skills, decision-making ability, and experience working in matrixed organizations. A related bachelor's degree or equivalent experience is required, with Python and Base SAS considered beneficial.

Develop, fine-tune, deploy, and optimize AI/ML models and LLM-based RAG applications using Python and AWS Bedrock. Build scalable REST APIs and microservices with FastAPI or Flask, deploy containerized solutions through AWS, Docker, and Kubernetes, and manage CI/CD. Design databases and automated ETL pipelines, collaborate with cross-functional teams, document workflows, and communicate AI concepts to stakeholders.

Develop cloud-based data solutions on Microsoft Azure for varied business use cases. Participate in architecture, analysis, design, development, implementation, testing, and Agile delivery. Provide technical expertise across project phases using Azure Data Factory, Functions, Logic Apps, Service Bus, SQL Database, Databricks, Python, and JavaScript. Collaborate with project teams and customer stakeholders while working independently. Preferred experience includes additional databases, Azure services, identity platforms, SharePoint, Okta, and Azure certifications.

Gather and analyze manufacturing business processes, KPIs, and MES requirements. Use factory automation, PLC, and Cygnet SCADA expertise to conduct AS-IS and TO-BE studies, design ERP-MES-control system interfaces, and create functional and business requirement specifications. Collaborate with plant users, subject matter experts, customers, and cross-functional teams to design, configure, and implement manufacturing solutions.

Develop and maintain high-performance 3D modeling software using advanced geometry processing, rendering, simulation, and visualization techniques. Integrate 3D assets, graphics APIs, game engines, and emerging VR, AR, and AI technologies. Build testing frameworks, troubleshoot complex issues, document software, conduct code reviews, provide technical support, and mentor junior developers while collaborating with designers, artists, engineers, and QA teams.

Develop and enhance Python-based finance data integration and transformation platforms. Build technical designs, data models, warehouses, SQL procedures, REST integrations, and cloud architectures. Work extensively with Oracle EPM Planning and Essbase for data loads, retrievals, processing, and APIs. Support Oracle Analytics platforms including OAC, OAS, OBIEE, OBIA, and ODI. Participate in architecture reviews, Agile delivery, estimation, client collaboration, and Git-based configuration management.

Develop end-to-end data science and AI/ML solutions involving statistical modeling, machine learning, generative AI, LLMs, NLP, and unstructured data analytics. Build data models and algorithms, solve ambiguous business problems, collaborate with project managers and multiple teams, and deliver actionable insights using cloud platforms such as AWS, Azure, or GCP. Present findings and communicate effectively with technical and business stakeholders.

Design and conduct advanced technical interviews and assessments for senior machine learning, NLP, and data modeling roles. Develop current evaluation criteria, collaborate with HR and technical teams, provide hiring recommendations, facilitate technical workshops, mentor junior assessors, and maintain an excellent candidate experience. The role requires deep expertise in ML and NLP methodologies, data modeling, programming tools, distributed computing, technical evaluation, and candidate feedback.

Provide L3 support and platform engineering for the Domino Data Lab platform. Troubleshoot production incidents involving workspaces, models, jobs, connectivity, access, and performance; conduct root-cause analysis and implement permanent fixes. Manage upgrades, patching, monitoring, tuning, and reliability for enterprise data science and AI/ML workloads. Support Python and R environments, ML workflows, Kubernetes, Docker, AWS, SageMaker, and Azure Machine Learning integrations in regulated or life sciences environments.

Design, develop, and maintain web applications using HTML5, JavaScript, CSS, XML/JSON, SQL, SAS, and server-side technologies. Extract, integrate, import, and export data across operational platforms while ensuring data integrity and security. Collaborate with cross-functional teams, document technical solutions, conduct integration and end-to-end testing, provide hypercare support, and recommend improvements to application performance and user experience.

Build and maintain machine learning infrastructure, deployment platforms, data pipelines, APIs, CI/CD workflows, and infrastructure-as-code. The role productionizes machine learning prototypes, orchestrates structured and unstructured data workflows with Airflow and Kubeflow, automates exploratory data analysis, integrates ML capabilities into large-scale products, and performs end-to-end testing. Strong Python and GCP expertise are required, with experience in Vertex AI, PySpark, SQL, and related tooling.

Lead Oracle EPM Planning and Essbase implementations, including cube processing, calculations, data loads, business rules, financial models, validation, and optimization. Develop Python-based integrations, transformations, automation, APIs, and data pipelines. Use SQL for data handling and support Oracle analytics integrations. Participate in solution design, architecture, estimations, Agile delivery, documentation, and stakeholder collaboration.

Conduct technical interviews and assessments for senior Selenium testing candidates. Develop assessment criteria, evaluate automation expertise and problem-solving skills, provide hiring feedback, facilitate technical workshops, stay current with Selenium practices, mentor junior assessors, and support a positive candidate experience.

Lead QA strategy and execution for carrier-grade optical networking (DWDM/OTN/GbE). Develop test plans, automation frameworks, and system-level validations. Drive manual and automated testing (AI-augmented), collaborate with engineering teams, analyze failures, and report on quality and release readiness across product releases.

Lead design and architecture of cloud-based systems, mentor architects and developers, translate stakeholder needs into technical solutions, optimize large-scale databases, conduct code reviews and performance tuning, document architectures, troubleshoot complex issues, and enforce security and best practices.

Lead QA strategy and execution for Optical DWDM equipment and protocol verification (OTN, GBE, DWDM, system security). Define test strategies and plans, develop cross-functional test scripts, manage automation frameworks and script execution, analyze failures, collaborate with engineering teams, and report on test results and defect resolution to ensure carrier-grade product quality.

Senior embedded software engineer for optical line systems. Own feature delivery across product lifecycle, design and implement software for optical hardware, mentor teams, collaborate with HW/FW and validation, resolve complex issues, and maintain quality using CI pipelines and agile practices.

Design and execute manual and automated test strategies and frameworks for optical systems (DWDM, OTN, Ethernet). Test NBI interfaces (YANG, NETCONF, RESTCONF, gRPC), FCAPS, and system security. Drive CI-based test automation, qualify OS releases (microservices/container architectures), collaborate with cross-functional teams, and own product qualification deliverables to ensure reliable, high-quality releases.

Own the technical direction of two products while serving as a hands-on player-coach. Design and build Verizol’s wallet and ledger core, API architecture, provider integrations, and event pipeline. Oversee ZipNom Serve’s FastAPI, MQTT, Flutter, and ESP32 architecture, pilot instrumentation, and device operations. Establish engineering standards, review code, mentor 4–6 engineers, guide AWS infrastructure, manage delivery scope, and support vendor decisions.

Build and maintain production backend APIs for corporate intelligence and business verification. Responsibilities include fixing bugs, writing tests, developing endpoints, integrating third-party verification vendors, normalizing external API responses, improving OpenAPI specifications and documentation, and owning a small set of endpoints, admin tools, or alert/webhook functionality with mentorship and code review.

Build and operate a production data pipeline ingesting Indian MCA registration data. Responsibilities include raw-first S3 storage, resilient scraping and parsing, snapshot and diff processing, granular change events, scheduled batch jobs, alert digests, monitoring, anomaly detection, reference-table maintenance, and historical backfills. The role requires strong Python, PostgreSQL, testing, operational reliability, and production experience with uncooperative data sources.

Lead the architecture and implementation of a production-grade generative AI media platform. Build reproducible, versioned pipelines, train LoRAs, integrate control techniques (ControlNet, IP-Adapter, inpainting), automate QC against product references, deploy internal tools, and partner with design to own the technical roadmap and enable creative teams.

The role involves shaping Data Management strategy, leading solutions development, driving AI innovation, building collaborations, and coaching junior team members.

Develop and maintain Golang applications, design and implement software solutions with cross-functional teams, troubleshoot issues, ensure code quality and performance, participate in code reviews, and contribute to system design discussions in a remote contract role.

Develop, deploy, and scale AI/ML and generative AI solutions for a fintech platform. Design data models and pipelines, build agentic frameworks, integrate OCR and vector DBs, implement RAG, and champion MLOps and cloud deployment practices while mentoring teammates.