Jobs at Quantiphi

Build and deploy end-to-end machine learning solutions, with a strong focus on computer vision, image processing, model development, feature engineering, cloud platforms, MLOps, monitoring, and CI/CD. Collaborate with stakeholders and IT teams across multiple engagements, follow Agile methodologies, ensure project delivery quality, and contribute to research and development.

Design, architect, and implement highly available video streaming and inference platforms. Build and maintain Kubernetes and Docker infrastructure, CI/CD pipelines, monitoring, alerting, deployment strategies, and distributed systems. Develop production-grade Python backend services using Flask and Gunicorn, integrate databases and streaming pipelines such as Redis and Kafka, and troubleshoot Linux-based container environments. Collaborate with machine learning research and production DevOps/MLOps teams.

Own backend and infrastructure architecture while developing Python and PHP services, APIs, authentication integrations, and database solutions. Design and maintain GCP infrastructure, Docker environments, CI/CD pipelines, monitoring, security, backups, and disaster recovery. Lead technical decisions, cloud optimization, incident response, documentation, and collaboration with frontend teams on headless CMS and SaaS deployments. Advise stakeholders on technical approaches, costs, risks, and estimates while mentoring engineers and supporting client-facing initiatives.

Designs, develops, optimizes, and deploys advanced machine learning and generative AI solutions on AWS. Builds RAG pipelines, AI agents, knowledge bases, and workflow orchestration using Bedrock and agentic AI frameworks. Responsibilities include document processing, vector search, prompt engineering, model integration, guardrails, authentication, scalable architecture, monitoring, and secure production deployment.

Design and implement resilient, secure services, adapters, and agents using C# and .NET. Modernize legacy .NET Framework applications, develop REST APIs, integrate databases and messaging, and ensure strong observability, reliability, and test coverage. Support Windows, Linux, and containerized deployments, participate in design reviews and releases, and mentor peers. The role also involves preserving legacy behavior during migrations and building unattended components for customer environments.

Drive end-to-end B2B sales and go-to-market activities for data science and applied AI solutions. Responsibilities include prospecting, customer relationship management, technical presentations, solution scoping, proposal development, business analysis, and resolving technical objections. The role partners with solution architects and data science teams to develop AI and cloud solutions, demonstrate Google Cloud integrations, manage client expectations, and identify new business opportunities across multiple industries. Travel to customer sites and events may be required.

Design, implement, and support secure, scalable Azure platform solutions. Lead cloud migration and legacy application modernization, including containerization on AKS. Build Terraform-based infrastructure and GitHub Actions CI/CD pipelines, manage Azure services, networking, identity, databases, monitoring, and production support. Troubleshoot incidents, perform root cause analysis, document architectures and runbooks, collaborate across technical teams, and mentor junior engineers.

Designs and secures AWS platform infrastructure using Terraform and CloudFormation. Builds event-driven security automation with EventBridge, Lambda, and Systems Manager; integrates Security Hub and GuardDuty with Jira; enforces tagging and governance across AWS accounts and partitions; manages Firewall Manager, secure CI/CD pipelines, compliance standards, account vending, and incident-response automation. Collaborates with platform, network, and security teams to establish architecture patterns, remediation workflows, and security controls.

Leads software product development projects and advanced analytics, machine learning, and technology solution delivery. Responsibilities include gathering requirements, defining problems, creating user stories, managing project teams and client expectations, preparing technical documentation, applying Agile and Scrum methodologies, identifying risks, consulting clients, and developing creative solutions and presentations.

Leads data preparation, profiling, and exploratory analysis for large-scale datasets; builds, evaluates, tunes, and deploys time-series forecasting models for demand planning. The role requires Python, SQL, AWS, SageMaker, ML frameworks, and MLOps tools. It involves independent end-to-end ownership, customer presentations, stakeholder collaboration, and translating technical work into business outcomes. Retail or e-commerce forecasting and computer vision experience are preferred. Travel to the Bengaluru client office twice weekly is required.

Design and deliver large-scale data pipelines and storage/compute solutions on Google Cloud. Build ingestion and processing jobs for terabyte/petabyte workloads, create cloud migration strategies, troubleshoot distributed systems, and develop automation, testing, and monitoring tooling. Collaborate with cloud, software, ML, and operations teams and contribute to proposals and solution designs while ensuring data modeling and governance.

Design and implement scalable enterprise data platforms, ETL/ELT pipelines, data warehouses and lakes. Define data models, governance, security, and architecture standards. Collaborate with product, BI, and data science teams, provide production support, mentor engineers, and evaluate emerging technologies and POCs.

Lead Oracle database migrations to AWS, ensuring minimal downtime and optimized performance. Responsibilities include database tuning, pipeline building, and managing S3 data lakes.

The Associate Lead will oversee QA and MLOps for AI systems, defining testing strategies, validating ML lifecycles, and leading quality initiatives with AWS services.

Lead Platform Engineering to architect, deploy, and manage secure, scalable AWS cloud infrastructure using IaC, CI/CD, monitoring, automation, and container platforms; enforce AWS security governance; mentor engineers and collaborate on solution design.

The Data Modeler designs and maintains the Common Data Model and source-to-target mappings for healthcare data assets, working closely with engineers and clinical informaticists to ensure accuracy and integrity in data representation.

Design and maintain scalable analytics solutions on Looker BI Platform, optimize data models, develop dashboards, and ensure governance and compliance with data standards.

The Data Architect is responsible for designing data architecture, leading the creation of the Common Data Model, ensuring standards compliance, and handling high-volume data ingestion while collaborating closely with technical and governance teams.

The Associate Architect - Machine Learning role involves developing cloud ML solutions on AWS, fine-tuning LLMs, and collaborating with teams for optimal model implementation.

Responsible for defining the testing strategy and infrastructure across the platform, including the development of a four-tier test framework and leading load testing campaigns. The role requires collaboration with data engineering teams and establishes QA strategies for data quality and testing frameworks.