The Position

OPSWAT is now searching for a Software Engineering Intern to join our MDaaS product. MDaaS is a real-time malware scanning platform handling 30M+ requests/day, built on a Node.js/TypeScript microservices architecture with event streaming (Kafka, RabbitMQ) and React frontend.

As an Intern, you'll work directly with senior engineers — shipping real features, fixing real bugs, and learning how a production-grade cybersecurity platform is built and operated.

What You Will Be Doing

• Implement small features and bug fixes across backend services (Node.js/TypeScript) under guidance from senior engineers

• Write unit and integration tests to improve coverage on existing modules

• Participate in code reviews — both receiving feedback and reviewing peers

• Debug issues in local and staging environments using logs and tracing tools

• Read and understand event-driven flows (Kafka consumers, RabbitMQ handlers) to contribute to ingestion and processing pipelines

• Update and maintain internal documentation, API specs, and runbooks

• Join sprint planning, daily standups, and retrospectives as an active team member

• Experiment with frontend components in the internal tooling dashboard (React + TypeScript)

What You'll Learn

By the end of your time on MDaaS, you'll have hands-on exposure to:

• Production TypeScript microservices — structure, patterns, and testing

• Event-driven architecture with Kafka and RabbitMQ

• Docker and basic Kubernetes concepts (deployment, logs, exec)

• Code review culture and engineering standards in a global product company

• How a cybersecurity SaaS platform processes millions of file scan requests

What We Need From You

Education & Background

• Pursuing or completed a degree in Computer Science, Software Engineering, or equivalent

• Able to commit at least 4 months (internship) or full-time (associate)

Soft Skills

• Curious and proactive — asks questions, doesn't wait to be unblocked

• Communicates clearly in English (written); able to describe problems and solutions concisely

• Receptive to feedback and willing to iterate quickly

• Comfortable working in a team across different timezones

Technical Fundamentals

• Solid understanding of programming fundamentals: data structures, algorithms, OOP

• Hands-on experience with JavaScript or TypeScript — coursework or personal projects count

• Familiar with Git: branching, pull requests, resolving conflicts

• Basic understanding of REST APIs: HTTP methods, status codes, request/response structure

• Able to read and understand existing code in an unfamiliar codebase

• Actively uses AI coding tools (GitHub Copilot, Cursor, Claude, ChatGPT) as part of daily workflow — knows how to prompt effectively, verify output, and not blindly trust generated code

Dev Environment

• Comfortable working in a Linux/macOS terminal

• Knows how to run a project locally with Docker Compose

• Can use a debugger or structured logging to trace a bug

If Would Be Nice If You Had

• Prior internship or project experience with a Node.js or TypeScript backend

• Familiar with any testing framework (Jest, Vitest, Mocha)

• Basic React knowledge — able to build or modify a UI component

• Exposure to message queues (Kafka, RabbitMQ, Redis) — even conceptually

• Knows what a microservice is and why services communicate over events

• Experience with any cloud provider (AWS, GCP, Azure) — even free tier

• Interest in cybersecurity — malware analysis, threat intelligence, or security tooling

• Has read about or experimented with CI/CD pipelines

• Experience building features or scripts with AI assistance end-to-end — from prompt design to testing the result

• Understands limitations of LLM-generated code: hallucinations, outdated APIs, security blind spots

• Has experimented with AI APIs (OpenAI, Anthropic, Gemini) in side projects

• Familiar with concepts like RAG, embeddings, or function calling — even at a basic level

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems
  
  
  

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Position

OPSWAT is committed to harnessing the power of AI to drive meaningful advancements across all areas of our business. We are currently seeking a highly skilled AI Engineer (Middle Level) to lead and support the development of AI-driven projects, with a key focus on integrating our in-house AI Insights go-to-market platform with various enterprise systems.

In this role, you will work closely with the Digital Transformation Team, Customer Experience (CX) Team, and the Enterprise & Data Team to integrate AI capabilities across CRM and other critical business platforms. This is a unique opportunity to be at the forefront of AI innovation within a global cybersecurity company, delivering impactful solutions that improve efficiency, intelligence, and customer outcomes.

What You Will Do

• Development of AI Insights - Go-To-Market Platform:
  • Design, build, and evolve AI Insights, OPSWAT’s in-house, AI-powered go-to-market platform built on CRM and enterprise data.
  • Architect and implement multi-agent AI systems that analyze GTM data to:
    • Identify customer buying intent, readiness, and deal momentum
    • Prioritize customer accounts and opportunities with clear, explainable reasoning
    • Detect pipeline risk, slippage, and growth opportunities across sales and marketing
  • Develop and maintain data pipeline to transform raw CRM data into decision-ready signals, metrics and insights used by AI agents.
• Development of Chatbot Platform:
  • Design, build and maintain OPSWAT AI Assistant - our chatbot framework to build chatbot systems.
  • Continuously improve Agentic RAG, MCP services and data pipeline for enterprise data systems.
  • Fine-tune a custom LLM model with deep understanding of OPSWAT products and cybersecurity world.
  • Fine-tune SLM model for intention classification, agentic tool calling, etc.
• Research & Propose Innovative Solutions: exploring and implementing novel AI techniques and automation solutions.

What We Need From You

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering, with a focus on Generative AI, LLM, Machine Learning and web app development.
• Experience in multi-agent orchestration framework (e.g. LangGraph, AutoGen, Agent Framework, ...).
• Experience in RAG architectures and Vector databases (e.g. Azure AI Search, Pgvector, Weaviate, ...).
• Experience in fine-tuning or instruction-tuning LLMs.
• Solid understanding of software development methodologies (Agile, Scrum, etc.).
• Good communication, collaboration, and interpersonal skills.
• Strong problem-solving and analytical skills.
• Ability to work independently and as part of a team in a fast-paced environment.
• Proficiency in one or more of the following programming languages: Python, React, Typescript.

It Would Be Nice if You Have

• Certifications in AWS and Azure architecture.
• Experience in backend-end development.
• Experience in CI/CD pipelines and cloud production deployment (Azure, AWS or GCP).

About the Role

The CTO Intelligence Hub is OPSWAT’s internal AI-powered data platform; dashboards and APIs that give leadership real-time visibility into AI adoption, financial performance, customer health, and sales. The platform runs on a fleet of Flask, FastAPI, and Streamlit applications backed by a Fabric → Parquet → S3 data pipeline, all tied together by an agentic coding system where GitHub Issues become production pull requests in under three minutes.

As AI Platform Architect, you own the application layer. You design and build new intelligence products, evolve existing dashboards, and work with the AI coding pipeline — writing the specs, reviewing the plans, and guiding the implementation. You are the “human senior engineer” in a team where your main coding collaborator is Claude.

What You Will Own

• Application architecture: Flask APIs, FastAPI microservices, Streamlit dashboards; schema and data-flow design across 12+ applications
• Agentic coding pipeline: creating well-scoped GitHub Issues, reviewing AI-generated implementation plans, approving or refining, merging PRs; the pipeline (claude-coder) takes issues from triage to production PR in ~3 minutes for routine work
• Data pipeline & analytics: extending the Fabric → Parquet → S3 pipeline; designing new analytics (percentile ranking, quadrant analysis, trend computation); HR enrichment and data quality
• Test-driven development: writing pytest spec suites that the AI implementer must satisfy; test files are the spec and cannot be modified by the AI
• Claude API / CLI integration: building features that call Claude for inference (content generation, analysis, RFP answering); working with OAuth-based CLI inference and direct API patterns
• UX & visualisation: Plotly dashboards, Jinja2 templates, React/Vite prototypes; maintaining the OPSWAT brand system across all apps
• Architecture documentation: keeping Confluence up to date as the system evolves; writing CLAUDE.md context files that teach the AI pipeline how each repo works
• New product design: identifying gaps in current intelligence coverage and proposing, scoping, and shipping new internal tools

You Will Be a Strong Fit If You Have

• 3–7 years of Python backend development (Flask, FastAPI, or equivalent)
• Strong data skills: pandas, SQL, Parquet, data modelling; you are comfortable designing a metrics pipeline from raw HR and usage data to ranked leader-board
• Experience working with LLM APIs (OpenAI, Anthropic, or equivalent) in production
• A test-first mindset: you write tests before code and believe the test suite is the specification
• Clear written communication because your primary “pairing partner” reads GitHub Issues, your ability to write precise, unambiguous requirements directly determines output quality
• Comfort reading and reviewing AI-generated code critically; you know when to approve, when to push back, and when to take the keyboard yourself
• Experience with REST API design and documentation

Nice to Have

• Streamlit or Plotly dashboard development
• React / TypeScript (for UX prototypes)
• Microsoft Fabric, Azure Data Warehouse, or similar cloud data platforms
• Familiarity with GitHub Actions and CI/CD pipeline design
• Experience building multi-language document processing (the RFP automation covers 14 languages)
• Prompt engineering and system-prompt design for agentic workflows
• OPSWAT product knowledge (MetaDefender, OESIS, CDR - not required but helpful)

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: We're seeking a Senior Site Reliability Engineer to join the team. You will build and operate the infrastructure and tooling behind WorldQuant's data ingestion pipelines — systems that onboard, validate, and deliver large-scale datasets to the firm's research platform. This is a 70% build / 30% operate role. You'll spend most of your time engineering automation, observability, and developer tooling, while also participating in on-call rotations and incident response for production data pipelines. You'll partner with engineering, analyst, and research teams to ensure reliability at scale — this requires excellent analytical skills, clear communication, and the ability to collaborate across teams.

What You'll Do:

Build (70%):

• Design and develop automation, monitoring, CI/CD, and reliability features for the data onboarding pipeline
• Develop and maintain internal infrastructure and services that reduce toil and improve pipeline reliability
• Build observability solutions — dashboards, alerting, log aggregation — using Grafana, the ELK stack, and Vector
• Design and implement CI/CD pipelines, test automation, and release management workflowsWrite infrastructure-as-code for provisioning, scaling, and managing platform components: Kubernetes, bare metal hosts
• Integrate and extend tools such as Redis, Celery, MySQL

Operate (30%): Keep production data pipelines healthy and respond to incidents

• Participate in on-call rotation, respond to production incidents, and drive post-mortems
• Define and track SLOs/SLIs for pipeline reliability, latency, and data freshness
• Diagnose platform performance and reliability issues, driving them to root cause
• Create and maintain runbooks for common operational scenarios
• Plan capacity and optimize resource utilization

What You'll Bring

• 8+ years of experience in SRE, DevOps, or platform engineering roles
• Linux expertise: Power user proficiency in Linux with ability to manage infrastructure, deploy services, and troubleshoot production systems
• Python proficiency: Strong scripting and automation skills; experience building CLI tools, API clients, monitoring integrations, and operational tooling in Python
• Kubernetes & containers: Deep hands-on experience with Kubernetes — deploying, scaling, debugging, and managing production workloads. Familiarity with Helm, resource management. Solid experience with Docker
• Observability: Hands-on experience with monitoring stacks — Grafana, Prometheus, ELK (Elasticsearch, Logstash, Kibana), or similar. Experience designing dashboards, alerts, and SLO-based reliability tracking
• CI/CD & infrastructure-as-code: Experience designing and maintaining CI/CD pipelines (GitLab CI, or similar), including test automation and release management. Familiarity with Ansible or similar IaC tools
• Databases: Working knowledge of relational databases (MySQL/PostgreSQL), query tuning, and operational database management
• Message queues & streaming: Experience with Kafka, Redis pub/sub, or Celery for event-driven architectures
• Networking & APIs: Understanding of network fundamentals, DNS, load balancing, and REST/gRPC APIs
• Incident management: Experience with on-call rotations, incident response, post-mortems, and runbook-driven operations
• Leadership & management: Proven track record of leading a team — mentoring engineers, driving technical roadmaps, coordinating cross-team initiatives, and managing priorities. Comfortable owning team delivery and representing the team to stakeholders
• AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development and operations workflow — treating AI as a force multiplier for automation, incident analysis, and toil reduction
• Nice to Have:
  • Cloud platforms: Exposure to GCP or AWS for compute, storage, and managed services
  • Data tools: Familiarity with Apache Arrow, gRPC, or columnar data formats
  • Big data platforms: Familiarity with Hadoop or Apache Spark for large-scale data processing
  • Programming languages: C/C++, Golang, Scala, JavaScript
  • Financial services or data-intensive industry background
  • SRE culture: Familiarity with Google's SRE book principles — error budgets, toil tracking, blameless post-mortems

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

The Role: We are seeking for a candidate to join our team as a Data Engineer. The Data Engineer will partner with our close-knit team of quantitative researchers, technologists and data sourcing colleagues to analyze and enrich a broad range of structured and unstructured large-scale data.

Job responsibilities include, but not limited to the followings:

• Enriching a wide range of structured and unstructured data into datasets for quantitative analysis and financial engineering.
• Enhancing data quality & integrity by developing validation tools to measure the effectiveness of data enrichment.
• Becoming a domain expert on different deep learning and machine earning applications, analyzing & understanding the underlying dynamics and behaviors within the data.
• Develop insights based on the data and collaborate with the research team to generate signals.
• Developing the utility tools that can further automate the software development, testing and deployment workflow.

 What You’ll Bring:

• Strong academic background – minimum of a bachelor’s degree in a technical or quantitative field.
• Practical experience with and understanding of deep neural networks and other machine learning techniques.
• Demonstrated ability to implement data science pipelines and real-time applications in Python
• 3+ years of relevant experience as a Data Engineer or similar roles.
• Proficiency with python-based tools like Jupyter notebook, coding standards like pep8.
• Experience with LLM/AI for data processing is a plus
• Exceptional analytical & problem-solving abilities, with a strong attention to detail.
• Good command of English
• Excellent software development skills: ability to convert rough overall use-cases to a working codebase.\
• Motivated by a deep curiosity and passion to learn is a plus.
• Past experience as a data scientist or data engineer in finance or investment profile is a plus.
• Experience with Linux/Unix shell and Git is a plus.

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-NV1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: We're seeking a senior developer to join our team. You will design, build, and operate large-scale data and ETL systems that power the firm's research and investment workflows. This is a high-autonomy role - you'll own critical systems end-to-end, make architectural decisions, and deliver solutions with minimal guidance. We need someone who is self-directed, able to lead themselves, take ownership of outcomes, and drive complex problems to resolution independently. You should be comfortable communicating across teams, articulating technical trade-offs to stakeholders, and mentoring others through code review and collaboration.

What You'll Do:

• Design, develop, and own backend services and data pipelines that process large volumes of data optimally and at scale
• Architect data storage and processing solutions, including schema design, query optimization, and data modeling
• Build and maintain APIs, messaging systems, and integration layers that connect data producers and consumers
• Drive technical decisions - evaluate trade-offs, choose the right tools, and define system boundaries
• Take ambiguous requirements and break them down into deliverable, well-engineered solutions
• Diagnose and resolve complex production issues - applying strong analytical and systems thinking
• Improve engineering practices: testing, CI/CD, observability, and documentation

What You'll Bring:

• 8+ years of professional software development experience
• Strong programming proficiency: Mastery of at least one major programming language (Python, Java, Go, C++, or equivalent). Beyond syntax fluency, you should understand language internals and be able to apply that depth to write performant, reliable code
• System design: Proven ability to architect distributed, scalable, and fault-tolerant systems. Understanding of common patterns - event-driven architecture, service decomposition, data partitioning, caching strategies
• Data engineering: Experience building ETL/ELT pipelines, working with batch and streaming data, and handling large-scale data processing
• Database proficiency: Deep understanding of relational databases (PostgreSQL, MySQL) and familiarity with analytical/columnar stores; strong SQL skills including query optimization
• Software engineering depth: Strong grasp of data structures, algorithms, design patterns, and software architecture principles - applied in production, not just theory
• API design: Experience designing clean, well-documented REST/gRPC APIs
• Incident response mindset: Ability to diagnose production issues methodically, drive root-cause analysis, and feed into post-mortems and operational improvement
• AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development workflow - using AI as a force multiplier for code generation, review, debugging, and documentation
• Nice to Have:
  • Python mastery: Advanced knowledge of Python internals, concurrency (asyncio, threading, multiprocessing), performance profiling, packaging, and strong experience with frameworks such as FastAPI/Flask, SQLAlchemy, pytest, and mypy/type annotations
  • Observability and distributed tracing: Experience with monitoring and observability stacks - metrics, structured logging, distributed tracing (OpenTelemetry, Grafana, ELK) - for diagnosing system behavior and bottlenecks in production
  • DevOps practices: Familiarity with containerization (Docker), CI/CD pipelines (GitLab CI, Jenkins), and infrastructure-as-code (Ansible, Terraform)
  • Programming language versatility: Proficiency in additional languages that complement data platform work - C++ for performance-critical systems, Scala for distributed data processing with Apache Spark, or Rust for high-performance data engineering
  • Team leadership and management: Experience leading a development team, running sprints, conducting code reviews, mentoring engineers, and managing stakeholders' expectations
  • Message queues and streaming: Experience with Kafka, Redis, or similar event-driven architectures
  • Data orchestration: Exposure to Airflow or similar workflow orchestration frameworks
  • Frontend / full-stack awareness: Familiarity with modern web technologies (React, TypeScript) for building internal UIs and dashboards
  • Financial services or quantitative finance background
  • Open-source contributions or a public portfolio of technical work

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

• Degree in a quantitative or technical discipline (computer science, engineering, etc.)
• Basic knowledge of probability and statistical theory
• At least 2 years’ experience in developing and managing scalable and robust data pipelines
• Have a deep understanding of machine learning, and experience in training, inference, and evaluation.
• Experience with LLM technologies and agentic systems 
• Excellent Python coding skills; familiarity with pandas / polars / duckdb is required
• Strong analytical skills and attention to detail
• Excellent communication skills in both verbal and written form
• Ability to operate in a collaborative, team-oriented culture
• Proactive and mature approach to problem-solving and project management
• Experience with Kubernetes (k8s) for deployment is preferred 
• Experience with monitoring and alerting tools is preferred 
• Familiarity with infrastructure management and deployment and ML Ops is preferred

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-VP1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: As an NLP Data Engineer at WorldQuant, you will be at the heart of transforming unstructured text into actionable, high‑value insights that power quantitative investment strategies. This is a hands-on, engineering role where you’ll design, build, and scale the data pipelines that underpin our data research. This role is ideal for someone who loves building production systems, enjoys working deeply with text and large language models, and wants their engineering work to empower quantitative research at the firm. You’ll join a highly technical, collaborative environment where you work closely with Research and where your ideas can quickly translate into impact at scale.

What You’ll Bring:

• BSc/M.Sc. from a leading university in Computer Science, Engineering, or related discipline
• 5 years of demonstrated experience programming scalable and robust software in Python
• Demonstrated experience building or maintaining data pipelines
• Basic knowledge of probability and statistical theory
• Experience working in Linux environments
• Experience with building and operating ML inference pipelines.
• Experience with using LLM for structured data extraction.
• Strong communication skills; ability to express complex concepts in simple terms
• Experience in the financial services industry is a big plus
• Knowledge of workflow scheduling techniques (e.g. Airflow) is a plus
• Prior experience working with text data in a data science/quantitative project environment

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models. 

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Research Intern. The person must have a good understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. This position is responsible for assisting with daily research and analysis tasks – which includes scripting for monitoring and alpha signal analysis. Candidates need not have prior knowledge of financial markets, but must have a strong interest in learning about stock markets and other capital markets. Successful candidates will self-starters, have a research scientist mind-set, and be creative and persevering deep thinkers who are motivated by unsolved challenges. Our highly accomplished senior staff will provide the interns with mentoring and guidance to help them succeed.

What You’ll Bring:

• Candidates holding or pursuing a BS (Hons), MS or PhD in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Data Science or Mathematics are strongly preferred
• Exceptional candidates without an advanced degree will also be considered. Prior quant analysis or trading experience is a benefit.
• Programming skills is a must (Python/ C++/Java)
• Have deep learning, LLM, NLP or prompt engineering course work or experience is a plus
• Participated in national and international mathematics or programming competitions (preferred)

What We Offer:

• 6-month learning and development path – challenge your intellectual mind
• Competitive compensation package with clear career road-map – opportunities to transition to a full-time role
• Online Medical support
• Team building activities every month – employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Happy-hour with tea break, snacks and meals every day!

#LI-NV1

What You'll Do:

• Architect As-A-Service solutions based on Open Source Software.
• Work within the team on the various products that the team supports.
• Develop tools to improve our ability to rapidly deploy and effectively monitor services in a large-scale distributed environment.
• Work with teams to design, develop, and implement innovative software solutions related to the DevOps and Agile transformation of the enterprise.
• Participate in periodic on-call duties.
• Collaborate with peers both inside and outside your team.

What You’ll Bring:

• Solid understanding and experience working with Linux based systems.
• Proficiency in Python for building APIs, developing automation scripts, and creating operational tools.
• Experience with modern authentication and authorization protocols such as OIDC, SAML, and Kerberos to ensure secure access to our platforms.
• Strong working knowledge of container orchestration with Kubernetes (K8s) is highly preferred. Experience with other cluster management systems like Slurm is a plus, especially if you have a background in large-scale computational environments.
• Proven experience with Infrastructure as Code (IaC) to automate the provisioning and management of our infrastructure, using tools like Terraform, Ansible, and Helm.
• Hands-on knowledge with containerization systems such as Docker or Podman.
• Experience with CI/CD, GitLab (preferred), GitHub or Git.
• Experience with agile development.
• A strong background in observability, with experience in monitoring and logging using tools like Prometheus, Grafana, and the OpenTelemetry (OTEL) stack.
• Experience using AI/LLM-powered tools and its concepts (MCPs, A2A,…) to support your development workflow is a plus.
• A great team attitude (our job is to make life easier for other teams!).
• Strong written and verbal communication skills in English.

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1