Programme duration: 6 months, starting in 2026.   

Who qualifies: Final year students completing a Bachelor's, Master's.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

Over the years, QRT has invested in a global research and execution platform which has been deployed to cover all geographies and asset classes. This platform covers a broad spectrum from high to low frequency trading systems. We thrive at the intersection of cutting-edge technology, smart automation, and scalable processes, enabling us to move fast, think big, and deliver at scale.   

We are committed to identifying and developing exceptional talent, and are inviting a new cohort of outstanding individuals to join us in the year ahead. Our internship offers a stimulating, intellectually rigorous, and high-performance environment, where collaboration is key to success. You will work alongside and be mentored by industry-leading professionals, gaining invaluable experience and positioning yourself for the opportunity to secure a full-time graduate role upon successful completion of the program. 

Your future role at QRT  

As a Machine Learning Engineer at QRT, you will contribute to building the systems used to evaluate and compare LLMs across a range of tasks and datasets. Design evaluation pipelines, define scoring methodologies, and develop the services that run, track, and reproduce experiments at scale. Integrate new models into a unified framework and optimize evaluation workflows for performance and reliability.

Your present skillset  

• Strong Python skills, with experience building reliable and maintainable systems.

• Solid software engineering fundamentals, including APIs, testing, and modular design.

• Experience working with data pipelines and experimentation workflows.

• Excellent communication skills - you will interact directly with Traders and Researchers.  

• Strong analytical and problem-solving skills, with a structured approach to ambiguous problems.

• Interest in large language models (LLMs), machine learning systems, and evaluation methodologies.

Preferred qualifications (a plus): 

• Experience with LLM tooling or frameworks (e.g. Hugging Face, OpenAI APIs, vLLM, or similar).

• Familiarity with evaluation or benchmarking frameworks (e.g. lm-eval, HELM, or custom evaluation pipelines).

• Exposure to distributed systems, parallel computing, or GPU-based workloads.
• Experience with experiment tracking tools (e.g. MLflow, Weights & Biases) or similar systems.
• Interest in model evaluation, robustness, and real-world performance of machine learning systems.

Interview Process 

•  Application - Submit your application online. We review applications on a rolling basis, so we recommend applying early to maximize your chances. 

• Technical Assessment - Selected candidates will be invited to complete a coding challenge designed to evaluate core technical and problem-solving skills. 

• Interviews - Shortlisted applicants will proceed to interviews, conducted either on-site or via Microsoft Teams. These will assess both your technical expertise and your alignment with our culture and values. 

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.  

Your Impact

We are looking for a Staff DataOps Engineer to join the Data and ML Platform team.

Your mission will be to shape our data platform strategy and architecture, driving enterprise-scale solutions that accelerate machine learning initiatives, enable engineering excellence, and unlock business insights. You will work in a team at the heart of Doctolib's data-driven transformation, enabling innovation through robust, scalable data infrastructure that empowers engineers, AI teams, and business stakeholders across the organization.

Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients.

What you'll build

Your responsibilities include but are not limited to:

• Design and implement enterprise-scale data infrastructure strategies, conducting thorough impact and cost analysis for major technical decisions, and establishing architectural standards across the organization
• Build and optimize complex, multi-region data pipelines handling petabyte-scale datasets, ensuring 99.9% reliability and implementing advanced monitoring and alerting systems
• Lead cost analysis initiatives, identify optimization opportunities across our data stack, and implement solutions that reduce infrastructure spend while improving performance and reliability
• Provide technical guidance to data engineers and cross-functional teams, conduct architecture reviews, and drive adoption of best practices in DataOps, security, and governance
• Evaluate emerging technologies, conduct proof-of-concepts for new data tools and platforms, and lead the technical roadmap for data infrastructure modernization

What you'll bring

Before you read on: if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

You'll be a great fit if you:

• You have 7+ years of experience after graduation as a Staff Data Platform Engineer, Staff DataOps, Staff Site Reliability Engineer, or in a similar role, with a history of architecting and scaling robust data platforms
• You have extensive experience with Google Cloud Platform and a command of Kubernetes & Terraform for automated deployments, and you are an authority on implementing network and IAM security best practices
• You have deep technical proficiency in orchestrating data pipelines using Airflow or Dagster, deploying applications to the cloud, and leveraging modern data warehouses such as BigQuery
• You are highly skilled in programming with Python, and have a solid understanding of software development principles
• You are an excellent troubleshooter who excels at diagnosing and fixing data infrastructure and identifying performance bottlenecks, and a strong communicator who can articulate complex technical concepts to both technical and non-technical audiences

It would be fantastic if you:

• Have hands-on experience building and deploying APIs, with a strong preference for frameworks like FastAPI, and are skilled at designing APIs that provide reliable and efficient access to data
• Have actively applied data governance principles to manage data quality, security, and compliance, and understand how to implement controls that protect sensitive information
• Are experienced with CI/CD tools and methodologies for data-related projects, and can build automated pipelines that streamline development, testing, and deployment
• Have practical experience with cloud cost optimization and FinOps principles, actively experimenting with cost-reduction strategies, and are comfortable analyzing infrastructure spending and optimizing resource allocation

Life at Doctolib Tech

• Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here.

Want to learn more about our tech culture and environment? Visit the Doctolib Tech site.

What we offer

• Free comprehensive health insurance for you and your children
• 25 days of paid vacation per year, plus up to 14 days of RTT
• Free mental health and coaching services through our partner Moka.care
• Work from abroad for up to 10 days per year thanks to our flexibility days policy
• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• 50% reimbursement of your public transport subscription
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Relocation support in case of international mobility
• Access to the best AI tools for coding, development and dedicated training

Our interview process

• Recruiter Interview
• Case Study
• System Design Interview
• Behavioral interview with Hiring Manager
• At least one reference check

We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page.

Job details

• Permanent position
• Tech stack: Google Cloud Platform, Kubernetes, Terraform, Dagster, BigQuery, dbt
• Full-time
• Paris
• Start date: as soon as possible

We welcome everyone

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, or disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g., pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

Your data privacy

All information provided is processed by Doctolib for application management. For data processing details, click here: France. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

Mid-level Full Stack Developer
Full-time
In-person

At Interstellar Lab, our mission is to build a future full of life, on Earth and beyond.
We believe in a world where technology enables humans to live in harmony with nature, where biodiversity thrives and expands, and where terrestrial life becomes multi-planetary.

To build this future, we design autonomous biospheric systems to grow plants with precision, on Earth and in Space. Our AI-powered BioPods and BioCapsules leverage biosciences to reproduce and optimize growth conditions for a wide variety of high-value plants.

On Earth, we pioneer molecular and biofarming, boosting the production of metabolites and bioactive compounds while offering sustainable, traceable, and high-quality natural ingredients to the beauty, fragrance, pharmaceutical, and nutraceutical industries.

In space, we collaborate with agencies and private companies to develop biofarming units that advance life science research in microgravity and lay the foundation for future biofactories in space, enabling innovative terrestrial applications and long-duration space missions.

About the Role
As Mid-level Full Stack Developer at Interstellar Lab, you will design, build, and scale the digital backbone of our biospheric systems. You will develop backend and automation services, contribute to our React-based BioApp, and integrate emerging AI capabilities into our products. You will work closely with engineers, scientists, and designers to connect devices, data, and interfaces seamlessly.

Responsibilities

• Develop and maintain backend services and APIs in Python (FastAPI)
• Contribute to frontend applications in React, ensuring smooth feature integration
• Connect sensors, devices, and automation layers across our digital ecosystem
• Integrate AI and agentic features to enhance functionality and autonomy
• Ensure scalability, robustness, and reliability of digital infrastructures
• Collaborate with engineers and designers on architecture and implementation
• Write and maintain technical documentation and clean, maintainable code
• Test, troubleshoot, and iterate rapidly within a fast-paced environment

Profile / Qualifications

• 3-6 years of experience in full-stack development
• Proficiency in Python (FastAPI) and modern backend frameworks
• Solid experience with React and frontend development principles
• Working knowledge of Docker and containerized environments
• Familiarity with AWS or equivalent cloud platforms
• Interest in AI APIs, automation, and connected systems
• Strong problem-solving and communication skills within multidisciplinary teams
• Fluent in English, French is a plus

Equal Opportunity
Interstellar Lab is proud to be an equal opportunity employer. Interstellar Lab does not discriminate on the basis of race, regional color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with disability, or other applicable legally protected characteristics.