Scandit Zürich

Senior Computer Vision Engineer

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.

We are now building a new generation of technology for retail: a computer vision–driven system that helps retailers to increase their profit margins through better operational insight and automation. As a Senior Computer Vision Engineer, you will play a leading role in taking this product from 0 to 1, owning key technical decisions and delivering production-grade vision capabilities end to end.

You will own the technical direction for action recognition in real‑world retail environments: from defining how we collect and annotate video data, to prototyping and evaluating models, to iterating on precision, recall and end-to-end alert latency under production‑like conditions. You'll work closely with product, data, and engineering stakeholders to validate the riskiest assumptions quickly and cost‑effectively.

If you enjoy turning ambiguous, high‑impact problems into working ML products – and have experience building commercial computer vision systems for action recognition, autonomous checkout, worker safety, or similar applications – we'd love to talk.

About the role

As a Senior Computer Vision Engineer, you will be responsible for leading the technical discovery and early development of Scandit's new solution – from validating the riskiest assumptions to building and iterating on the first end-to-end prototypes. You will work closely with product, other engineering teams, and external stakeholders to turn real-world video data into robust, privacy-aware computer vision models that can operate in live retail environments.

This role connects cutting-edge CV/ML research with real-world product constraints – requiring both deep technical expertise and a pragmatic, experimental approach to building production-ready systems under ambiguity and time pressure.

What you will do

• Defining and prioritizing technical experiments to validate key risks (e.g. precision, recall, latency) for computer vision models in retail stores
• Designing and implementing end-to-end CV/ML pipelines on real-world video data, from data ingestion and preprocessing through model training, evaluation, and deployment
• Setting up and refining the human annotation workflow to create high-quality training and test datasets from video streams
• Collaborating with product managers and engineering leaders to clarify requirements, align on milestones, and translate business needs into technical roadmaps
• Selecting, adapting, and optimizing state-of-the-art computer vision architectures for suspicious behavior and action detection in unconstrained environments
• Providing technical leadership in the space of video-based computer vision applications, helping shape best practices and future hiring for the team

Who you are

We are looking for a senior computer vision / machine learning engineer who has successfully built and shipped real-world products, ideally involving action recognition on video. You combine deep hands-on technical expertise with a pragmatic, experimental mindset and are comfortable working in a high-ambiguity, 0→1 product environment. You should enjoy collaborating closely with product and engineering stakeholders, shaping the technical direction, and iterating quickly on ideas to validate the riskiest assumptions.

• University degree in Computer Science, Electrical Engineering, Mathematics or a related technical field (advanced degree is a plus but not mandatory)
• Significant hands-on experience in computer vision and machine learning, including designing, training, evaluating and deploying models in production
• Proven track record of building end-to-end CV/ML systems from 0→1 (ideally commercial products rather than purely academic projects)
• Strong expertise with video-based pipelines and human action or behavior recognition (e.g. retail, autonomous checkout or similar domains)
• Solid software engineering skills (e.g. Python and modern ML/CV frameworks) and experience working with real-world, noisy data
• Ability to work in a dynamic, high-uncertainty environment, prioritize experiments, and iterate quickly on technical approaches
• Ability to collaborate effectively with cross-functional teams (e.g. product, backend, data, operations) and communicate complex technical topics clearly in English (B2 level or higher)
• Eligible to work in the hiring location

Nice to have:

• Experience with privacy-aware or GDPR-compliant data pipelines, especially for video data
• Background in building or selecting annotation tools and workflows for computer vision training data
• Prior work on retail, autonomous stores using computer vision

What we offer

Here are just some of the reasons why people choose to build their careers at Scandit:

• A highly skilled team and a fun environment where you can put your enthusiasm for cutting-edge technologies to use
• Hackathons 
• Flexible, office, hybrid or home working
• People-first culture
• Global team outings 
• Festive/end of year all company celebrations 
• Your birthday off 
• An attractive individual equity plan in a high growth company 
• We are certified as a “Great Place to Work” in 7 countries!
• Excellent office infrastructure, optimized for hybrid working in Zurich, Warsaw, Tampere, and London.
• Excellent support for remote work across Switzerland, Finland, Poland, UK, Italy and Germany
• Specific benefits related to the location you are joining

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applicants will receive consideration for employment without regard to race, color, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

Imagine the What. Build the How.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Duration: Minimum 6 months; ideally 9–12 months, depending on the candidate’s experience

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

About the Internship

We are offering a research-focused internship aimed at advancing machine learning methods for complex visual understanding tasks. The project centers on deep learning architectures for image-to-sequence modelling, such as Transformers, attention mechanisms, and modern sequence and representation-learning frameworks, to address challenging and highly structured computer vision problems. This project contributes to long-term research efforts aimed at achieving even higher performance, robustness, and generalization in large-scale visual applications.

What you will do

You will work closely with experienced ML researchers and engineers on cutting-edge research at the intersection of computer vision and sequence modeling. Your work will include:

• Designing and experimenting with new ML architectures for structured visual data.
• Evaluating alternative modeling paradigms (e.g., encoder–decoder, hybrid Transformer models, sequence-based representations).
• Investigating techniques for improving robustness, generalization, and multi-view reasoning.
• Running systematic experiments, ablations, and error analyses to validate research hypotheses.

This project provides opportunities for novel model design, extensive experimentation, and scholarly research. You will contribute to long-term innovation in our technology, with potential real-world impact for millions of users. An ideal position for experienced master’s students, PhD collaborations, or candidates preparing for a research career in industry or academia.

Who you are

MSc or PhD student in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a strong research focus. Candidates should have a solid foundation in machine learning theory, neural networks, and computer vision.

Essential Skills:

• Proficiency in Python and deep learning frameworks such as PyTorch.
• Practical experience designing, training, and evaluating neural networks, including CNNs and Transformer-based architectures.
• Strong analytical and problem-solving abilities, with the capability to interpret experimental results and iterate effectively.
• Familiarity with research best practices, including reproducibility, controlled experiments, and ablation studies.

Desirable Skills:

• Prior research experience in computer vision, pattern recognition, sequence modeling, or image-to-sequence architectures.
• Experience training large-scale models or working with foundation-style architectures.
• Contributions to publications, preprints, or open-source machine learning projects.

Strong communication skills and the ability to work independently in a research-oriented environment.

What We Offer

• We are certified as a “Great Place to Work” in 10 countries!
• A highly skilled team and a fun environment where you can put your enthusiasm for computer vision challenges and cutting-edge technologies to use
• Hackathons, summer parties, company outings and other regular events
• Office in the city center of Zurich

Who We Are

Could your code give superpowers? Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. This means we have no shortage of technical challenges for engineers like you. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

“Everybody is welcome here” - Is a celebrated component of our DNA.

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

#LI-MB1

#Engineering

#Hybrid

Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.

About Capco

Capco is a global technology and business consultancy, focused on the financial services and energy sectors. We are passionate about helping our clients succeed in an ever-changing industry.

We are:

• Experts in capital markets, banking and payments, wealth and asset management and energy.
• Deep knowledge in financial services offering, including e.g. Finance, Risk and Compliance, Financial Crime, Core Banking etc.
• Committed to growing our business and hiring the best talent to help us get there
• Focus on maintaining our nimble, agile and entrepreneurial culture

The Role
Join our team as a Senior Data Solution Engineer and transform complex data into meaningful, business-ready insights. You will design and deliver robust data solutions, working across modern cloud platforms and analytics tools to bridge business needs with strong data engineering practices.

What You’ll Do

• Architect and deliver scalable data marts in Snowflake and develop production-grade dbt models
• Design and implement semantic layers and reporting solutions using Power BI
• Optimize performance and cost across data models, queries, and reporting tools
• Collaborate with cross-functional teams to deliver data solutions aligned to business needs
• Support CI/CD processes and implement best practices for testing, deployment, and governance

What We’re Looking For

• Strong experience in data or analytics engineering, delivering data marts and semantic models in enterprise environments
• Hands-on expertise with Snowflake, dbt, Power BI, and SQL
• Understanding of CI/CD pipelines and modern development practices (e.g., Azure DevOps)
• Experience working in agile delivery environments with cross-functional teams
• Fluent English and German communication skills

Bonus Points For

• Experience with Data Vault 2.0 architecture
• Familiarity with Azure Data Factory and Python
• Experience migrating on-premise data platforms to cloud environments
• Exposure to financial services or similar regulated industries
• Experience implementing data security and governance frameworks

Ready to take the Next Step 

If this sounds like you, we would love to hear from you.  This is an opportunity to make a difference and contribute to a highly successful company with a significant growth trajectory.

In Short:

On's mission is to become the leading premium sportswear brand rooted in design, performance and sustainability. To drive this commitment, we are looking for a dedicated Sustainability Data Specialist in Zurich who will support our data efforts for our sustainability ambitions and requirements. Contributing to our annual GHG accounting, you will be responsible for collecting, validating, and calculating Scope 1-3 data, and building end-to-end data flows to transform raw source data into actionable metrics. Leveraging your track record in carbon accounting and data engineering, you will execute data workstreams for sustainability disclosure and regulatory requirements. You will collaborate with Tech and business stakeholders to streamline data workflows and systems, while supporting the Product Sustainability, Traceability, and Responsible Manufacturing teams with data needs. If you are data-savvy with a track record in GHG accounting and are looking to make an impact in a growing sportswear brand, this role is for you!

Your Mission:

• Collect, validate, and calculate Scope 1-3 data and manage relationships with data owners.
• Model and map end-to-end sustainability data flows from source systems to reporting tools, transforming raw data into actionable metrics.
• Identify opportunities to streamline data workflows and systems in collaboration with Tech teams.
• Execute data workstreams for sustainability disclosure and regulatory requirements (e.g., CSRD).
• Support Product Sustainability, Traceability and Responsible Manufacturing teams with data collection, visualization, and engineering tasks.

Your Story:

• Bachelor’s or Master’s degree in Data Science, Environmental Engineering, Sustainability, or a related field.
• Min. 1 year of experience in sustainability data with a track record in carbon accounting, expert in GHG Protocol.
• Ability to code in Python for data processing and automation of tasks.
• Experience with BigQuery or similar data warehouse architectures, including writing and optimizing queries.
• Proficiency in data management tools (Excel, Google Sheets).
• Strong understanding of sustainability metrics, reporting standards (such as SBTi), and global regulations.
• High attention to detail with the ability to structure and validate complex data.
• Ability to collaborate with both technical teams and business stakeholders.
• Fluency in English.
• Passion for sustainability.

Meet The Team:

We are a small team with big responsibilities. We design and implement the sustainability strategy across On and help shape the future of the organization. We do research, create strategies and implement projects and innovate products and processes through the lens of sustainability. We are the strategic hub, setting the direction and pace for corporate impact by defining priorities, targets, and policies. We act as internal educators and enablers, providing tools and training, and then amplify our progress through clear communication internally and externally.

What We Offer:

A dynamic environment ranked as a "fastest-growing sports company" where your work directly impacts our global footprint. A culture that fosters excellence and potential. This role offers deep exposure to strategic planning and technical knowledge growth. The chance to build something incredible with a collaborative, high-energy global community where you can truly thrive.

If you are driven to bring On to the next level, curious about the opportunity and want to be part of our growing team send us your application, and join the ONiverse!

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.

About the Internship

We are looking for students with a passion for computer vision or machine learning to join one of the teams in Zürich for four to six months. You will be a part of product development and you will help us improve and extend algorithms and their automated testing infrastructure.

Scandit offers an excellent opportunity to apply the theory from your studies while gaining hands-on experience with industry best practices in a international team.

What You Will Do

We have many interesting projects to offer. Depending on your background and interests, you could work on one of the following projects:

• Improve barcode scanning algorithms in difficult scenarios such as surfaces with deformations, glare or reflections
• Enhance the real-time visual tracking and pose estimation system of our solutions through the integration of additional sensor measurements and cutting-edge machine learning algorithms
• Enhance our object and context detection systems by developing, refining, and integrating state-of-the-art machine learning algorithms tailored to our specific domain
• Enhance our real-time visualization system to analyze and develop our computer vision algorithms
• Reduce manual steps in our image annotation tools with smart algorithms
• Develop image classification, matching and/or reconstruction features in order to improve the algorithms for understanding the current state of shelves and products in supermarkets

Our Tech Stack

• Computer vision algorithms: C++17, CMake
• Machine learning training and tooling, cloud processing: Python, Pytorch
• Acceleration: SIMD, Vulkan, CoreML

Who You Are

• Highly motivated student, interested in an internship of four months or longer
• Enrolled in or completed a bachelor’s or master’s program in computer science, information technology, robotics or a related field
• Solid knowledge of data structures and experience in object-oriented programming
• You have taken courses in computer vision, image processing and/or machine learning
• Ideally you already had some exposure to solving a computer vision problem in a semester project or thesis
• If you are interested in working on the core image recognition algorithms, solid C++ programming skills will be needed
• Python programming knowledge is a plus

What We Offer

• We are certified as a “Great Place to Work” in 7 countries!
• A highly skilled team and a fun environment where you can put your enthusiasm for computer vision challenges and cutting-edge technologies to use
• Hackathons, summer parties, company outings and other regular events
• Office in the city of Zürich (Hardbrücke)

Imagine the What. Build the How.

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed. 

In short: 

This is your chance to kickstart your career in the sportswear industry!

Become part of On's unique rotational development program - the Product Creation Academy. This 2 year journey is designed to develop you into a true functional expert with the potential to grow in our dynamic organization. You will embark on a specialized learning journey, with rotations designed to build depth in Footwear Engineering. But that’s not all! One of your rotations will take you to vibrant Vietnam, where you will learn first-hand what it takes to bring our products to life. To top it off, you’ll receive personalized mentorship from one of our senior leaders, ensuring you make the most of this transformative experience.

Are you ready to shape the future of the fastest growing sportswear company in the world? Dream On!

Program start date: September 1st, 2026.

Application period: Due to the expected high volume of applications, the role will be open for a limited time. We encourage you to apply as soon as possible.

Your mission: 

Over the course of the program, you will rotate through multiple connected teams, building a deep understanding of how Footwear Engineering contributes to bringing products to life. 

From working with data and engineering inputs to uncover insights, to learning how to translate these into parametric 3D models, digital tools, and repeatable workflows, and collaborating closely with engineers, developers, and innovation teams — over the 24 months, you will gain hands-on experience in rethinking how footwear is engineered through a computational and systems-driven approach.

Operating at the intersection of data, AI, and physical product creation, you will contribute to building tools, toolboxes, and processes that transform complex engineering standards, testing data, and product feedback into actionable outputs for footwear development. You will help design and implement digital solutions that automate workflows and elevate how teams create and engineer products.

This experience will set you up for success to start as a true functional expert in computational footwear engineering and support your long-term growth as a key contributor to shaping the future of data-driven, digitally enabled product creation at On.

Your story: 

• Preferably you have an educational background in a relevant field such as Computational Design, Industrial Design, Engineering, Architecture, or similar.
• Approximately 2-3 years of hands-on work in computational design or engineering, whether through professional roles, academic research, or significant personal technical projects.
• You have hands-on project experience (academic or personal) where you built something — e.g. a parametric model, script, or small tool, showing a “builder mindset”.
• You have experience with computational design tools (e.g. Rhino 3D, Grasshopper or similar) and show interest in using them beyond visual design (e.g. solving geometry or process-related problems).
• You have programming competency, ideally in Python, and are comfortable writing scripts to automate tasks or process data.
• You have experience working with data, using tools such as Python libraries (e.g. Pandas) or similar, and are able to apply data or AI in a product design or engineering context.
• You demonstrate structured problem-solving skills and an interest in translating complex, real-world problems into simple, repeatable approaches or workflows.
• You are able to communicate technical ideas clearly, and can explain your thinking to both technical and non-technical audiences.
• You resonate with the On spirits, bring a positive and proactive attitude, and are eager to learn and grow in a fast-paced environment
• You communicate clearly and effectively and are fluent in English (written and spoken).
• You have the right to work in Switzerland or the EU.

Meet the team: 

Our mission is to define and create the future of sportswear bringing to life groundbreaking innovations. Acting at the forefront of material science, sport science and engineering we develop products that push the boundaries of performance and sustainability, blending in unique aesthetic appeal that embodies On’s design DNA.

What we offer: 

On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically – to stay active, to learn, explore and innovate. Our distinctive approach combines a supportive, team-oriented atmosphere, with access to personal self-care for both physical and mental well-being, so each person is led by purpose.

On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.

The Role

We are seeking an experienced Quantitative Trader to join the team at Schonfeld in Zurich. The ideal candidate will blend rigorous macroeconomic insight with hands-on quantitative trading experience across credit, rates, and related derivatives. You will develop and maintain systematic models, collaborate closely with Portfolio Managers on trade ideas and risk, and leverage your network of sell-side economists and strategists to stay ahead of market trends.

What You’ll Do 

• Design, code, and maintain systematic and semi-systematic trading models spanning corporate bonds, credit ETFs, CDS indices, equity / vol cross-asset overlays and curve-relative value strategies.
• Build data pipelines, back-testing frameworks, and real-time risk / P&L dashboards in Python / C++ for fixed-income and multi-asset products.
• Conduct deep-dive macro research—integrating fundamentals, flow data, and machine-learning techniques—to generate high-conviction trade ideas.
• Produce concise macroeconomic briefs for Portfolio Managers, distilling complex drivers such as global rates cycles, credit spread dynamics, liquidity, and volatility regimes.
• Partner with Technology and Risk to refine execution algos, hedging rules, and portfolio-trading workflows.

What You’ll Bring

• 10+ years’ experience in macroeconomic research, credit volatility trading, and cross-asset systematic strategy design.
• Experience working at global top-tier multi-manager hedge fund and leading sell-side algo / ETF desks.
• Proven track record building and calibrating complex economic / financial models—mean-reversion, momentum, convexity, liquidity, and relative-value frameworks.
• Advanced programming skills: Python, C++, SQL; working knowledge of R / MATLAB and VBA-Excel.
• Work experience in credit indices (CDX / iTraxx), bond / ETF micro-structure, and derivatives greeks / risk.
• Strong written and verbal communication skills—able to translate quantitative outputs into clear investment theses.
• Master’s in Finance from a top-tier university and a Bachelor’s degree in a STEM discipline.
• Passed CFA Level I examination.

Who We Are  
Schonfeld Strategic Advisors is a global multi-strategy, multi-manager investment platform that harnesses the transformative power of people to perform in all market environments. Our dynamic culture inspires better outcomes for our team, our investors, and our partners. We aim to consistently deliver risk-adjusted returns, with people driving performance.

We specialize in four core strategies: Quantitative Trading, Fundamental Equity, Tactical Trading, and Discretionary Macro & Fixed Income. We capitalize on inefficiencies and opportunities within the markets, drawing from a significant investment in proprietary technology, infrastructure, and risk analytics.

We invest through internal portfolio managers and external partner funds, pursuing alignment among investors, investment professionals, and the firm. Our footprint spans 9 countries and 19 offices.

Our Culture
Talent is our strategy. We believe our success is because of our people, so putting our talent above all else is our top priority. We are teamwork-oriented, collaborative, and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning & educational offerings and opportunities to make an impact.

We foster a sense of belonging among all our employees. Our employees value diversity across identity, thought, people and perspective which serves as the foundation of our culture. As a firm, we are committed to creating a hiring process that is fair, welcoming and supportive.

#LI-DNI

Programme duration: From 4-6 months, starting in 2026. Most individuals join in April, May, or June of each year.    

Who qualifies: Penultimate or final year students completing a Bachelor's or a Master's degree. 

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   

Throughout the recruitment process, we will work to align your skills, interests, and potential with the teams where you can make the greatest impact. 

As a Quantitative Research Intern, you could contribute in one of two complementary areas within one of QRT's systematic teams - spanning high, mid, and low-frequencies: 

Research 

Your core objective will be to develop high-quality predictive signals. You will leverage access to vast and diverse datasets to identify hidden statistical patterns and market opportunities. Collaborating with fellow researchers to exchange ideas and refine methodologies. You will be trained to lead the full research cycle - from idea generation to implementation.   

Trading 

You will contribute to the live deployment of QRT’s research by working on the systematic trading platform itself. This involves monitoring signal behaviour, tracking performance, and improving execution efficiency, while also helping to identify and manage potential risks. Working closely with senior Researchers and Traders, you will focus on refining and scaling systematic processes, applying your quantitative and programming skills to ensure strategies perform optimally in production. 

We’re looking for interns who are curious, creative, and collaborative. If you’re passionate about learning, excited to take on challenges, and ready to make a real impact, you’ll find plenty of opportunities to grow with us. 

Your present skillset   

• Pursuing an advanced degree in a quantitative field such as data science, statistics, mathematics, physics, or engineering   

• High level of technical knowledge in statistics, machine learning, NLP or AI techniques is a plus   

• Coding skills required in at least one leading programming language (Python and C++ or C#)  

• Experience in exploring large datasets across multiple time frames is a plus  

• Capacity to multi-task in a fast-paced environment while keeping strong attention to detail   

• Ability to work autonomously, in a collegial and collaborative setting, and with colleagues from diverse backgrounds and areas of expertise.  

• Excellent communication skills  

• Fluent in English, any other language is a plus  

Interviewing:   

• Apply online: applications are evaluated on a rolling basis by a member of our Talent Acquisition team. This is a great opportunity to stand out, as we read every application carefully and look for specific, thoughtful answers that reflect your genuine interests. 

• Interviews conducted on-site or through Teams allow us to evaluate your technical abilities and how well you align with our company culture.   

We encourage you to take part in one of our Data Challenges, which offer a valuable opportunity to engage with the types of problems encountered in the Quantitative Research role while showcasing your analytical and technical skills. Strong performance may lead to direct follow-up from our team, making it an excellent way to gain early visibility in the recruitment process: Challenge data (ens.fr)  

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 

Eligible candidates: Final-year PhD students or postdoctoral researchers

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. Our culture is centred around technology, automation, and industrialized processes. We operate in multiple languages from C++ to Python and embrace open-source software.  

Your future role within QRT 

You will join a team of quantitative researchers to learn how to design trading algorithms in a real-world data environment – a fast track to become a seasoned quantitative researcher. Surrounded by peers who have successfully transitioned from academia to applied research, you will receive mentorship from experienced professionals who will help you translate your theoretical expertise into real-world impact. The research environment at QRT is designed to be collaborative and intellectually stimulating. 

Within one of QRT's systematic teams - spanning high, mid, and low-frequencies - your core objective will be to develop high-quality predictive signals: 

• Leverage access to vast and diverse datasets to identify hidden statistical patterns and market opportunities. 

• Collaborate with fellow researchers to exchange ideas and refine methodologies. 

• Translate theoretical models into production-ready signals. 

• Lead the full research cycle - from idea generation to implementation. 

Your present skillset 

• Holding or pursuing a PhD (final year) degree in a quantitative field such as statistics, mathematics, physics, biology, computer science, or engineering. 

• A pragmatic attitude towards translating theoretical models into real-world data problems.   

• Proficiency in Python (preferred) or another leading programming language such as R, MATLAB, C++, or C#. 

• Experience working with large datasets across multiple time frames (a plus). 

• Ability to multitask in a fast-paced environment with attention to detail. 

• Intellectual curiosity to explore new data, solve complex problems, and connect ideas across disciplines. 

• Ability to work autonomously, in a collegial and collaborative setting, and with colleagues from diverse backgrounds and areas of expertise. 

• Strong communication skills. 

• Fluency in English (additional languages are a plus). 

Interviewing:   

• Apply online: All applications are reviewed by our Talent Acquisition Team, on a rolling basis. 

• Interviews: Conducted on-site or via Teams, they assess both your technical expertise and alignment with our collaborative culture. 

We invite candidates for the Quantitative Research position to take part in one of our Data Challenges. This task is designed to give you insight into the daily responsibilities of the role and allows us to assess your abilities and interest: Challenge data (ens.fr) 

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 

Job Summary

The Systems Engineer plays a critical role in designing, integrating, and validating complex hardware systems across the full product lifecycle. This engineer works closely with cross functional teams including electrical engineering, firmware, mechanical design, manufacturing, software engineering and product management to ensure that system level hardware solutions meet performance, reliability, regulatory, and cost targets. The ideal candidate combines strong technical depth with systems thinking, hands-on validation skills, and excellent communication.

Key Responsibilities

Hardware Architecture & System Design

• Design IoT hardware systems (Gateways and BLE Sensors) integrating microcontrollers/SoCs, sensors, wireless modules, and power management subsystems.
• Design end-to-end systems from physical sensor measurements to processed data delivery to customer APIs
• Specify and evaluate low power components to maximize uptime under variable sunlight conditions.
• Generate schematics, PCB layouts, BOMs, and documentation in accordance with industry standards.

Power Management & Energy Optimization

• Model and optimize energy budgets to ensure year-round autonomous operation.
• Validate system performance through simulation, bench testing, and long duration field trials.

Sensor & Connectivity Integration

• Integrate a variety of sensors (environmental, motion, positioning, etc.) with proper front‑end conditioning.
• Implement and test wireless communication modules such as LoRaWAN, NBIoT, LTEM, LTE Cat 1, Bluetooth LE, or proprietary RF.

Prototyping, Testing, and Validation

• Build and iterate hardware prototypes rapidly using development kits, custom PCBs, and test equipment.
• Perform environmental, thermal, vibration, and ingress protection testing for ruggedized IoT devices.
• Conduct structured debugging across power, digital, RF, and firmware hardware interfaces.

Manufacturing & Deployment Readiness

• Support DFM, DFA and DFT practices
• Support certification processes (CE, FCC, EMC, IECex and safety compliance).
• Provide technical guidance for field deployment, maintenance tools, and diagnostics.

Key Qualifications

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Systems Engineering, or related field.
  • 5+ years of experience in hardware systems engineering or embedded hardware development.
• Strong understanding of core subsystems:
  • Power management and battery systems
  • Microcontrollers and embedded architectures
  • Analog/digital circuit fundamentals
  • Sensors (motion, environmental, pressure, light, etc.)
  • RF systems (cellular, BLE, GNSS, WiFi), antennas, and integration considerations
• Working experience with developing software to evaluate systems, e.g., python, Java or Kotlin
• Hands‑on experience with lab equipment: oscilloscopes, logic analyzers, spectrum analyzers, power measurement tools.
• Proven ability to perform system debugging across hardware, firmware, and mechanical interfaces.
• Experience creating system requirements, block diagrams, and integration test plans.
• Knowledge of EMC/EMI considerations, grounding, shielding, and layout best practices.
• Familiarity with reliability and environmental testing (HALT/HASS, vibration, thermal cycling).
• Excellent communication skills and ability to document and present technical details clearly.
• Strong analytical and problem solving skills with a systems-thinking mindset.

Duration: Minimum 6 months; ideally 9–12 months, depending on the candidate’s experience

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

About the Internship

We are offering a research-focused internship aimed at advancing machine learning methods for complex visual understanding tasks. The project centers on deep learning architectures for image-to-sequence modelling, such as Transformers, attention mechanisms, and modern sequence and representation-learning frameworks, to address challenging and highly structured computer vision problems. This project contributes to long-term research efforts aimed at achieving even higher performance, robustness, and generalization in large-scale visual applications.

What you will do

You will work closely with experienced ML researchers and engineers on cutting-edge research at the intersection of computer vision and sequence modeling. Your work will include:

• Designing and experimenting with new ML architectures for structured visual data.
• Evaluating alternative modeling paradigms (e.g., encoder–decoder, hybrid Transformer models, sequence-based representations).
• Investigating techniques for improving robustness, generalization, and multi-view reasoning.
• Running systematic experiments, ablations, and error analyses to validate research hypotheses.

This project provides opportunities for novel model design, extensive experimentation, and scholarly research. You will contribute to long-term innovation in our technology, with potential real-world impact for millions of users. An ideal position for experienced master’s students, PhD collaborations, or candidates preparing for a research career in industry or academia.

Who you are

MSc or PhD student in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a strong research focus. Candidates should have a solid foundation in machine learning theory, neural networks, and computer vision.

Essential Skills:

• Proficiency in Python and deep learning frameworks such as PyTorch.
• Practical experience designing, training, and evaluating neural networks, including CNNs and Transformer-based architectures.
• Strong analytical and problem-solving abilities, with the capability to interpret experimental results and iterate effectively.
• Familiarity with research best practices, including reproducibility, controlled experiments, and ablation studies.

Desirable Skills:

• Prior research experience in computer vision, pattern recognition, sequence modeling, or image-to-sequence architectures.
• Experience training large-scale models or working with foundation-style architectures.
• Contributions to publications, preprints, or open-source machine learning projects.

Strong communication skills and the ability to work independently in a research-oriented environment.

What We Offer

• We are certified as a “Great Place to Work” in 10 countries!
• A highly skilled team and a fun environment where you can put your enthusiasm for computer vision challenges and cutting-edge technologies to use
• Hackathons, summer parties, company outings and other regular events
• Office in the city center of Tampere

Who We Are

Could your code give superpowers? Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. This means we have no shortage of technical challenges for engineers like you. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

“Everybody is welcome here” - Is a celebrated component of our DNA.

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

Senior Machine Learning Engineer (Computer Vision)

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

About the role

We are looking for a new colleague to join the Label Capture team and work on creating digital twins of complex labels and identification documents. You will be responsible for evolving our current product by adding new features and optimizing the existing offering. You will work on computer vision and deep learning algorithms to improve information extraction from printed documents beyond state of the art.

If these challenges sound interesting to you, we’d love to hear from you!

What you will do

• Driving and solving semantic document parsing for our customer use cases
• Be involved hands on in all phases of end to end quality improvements (defining and tracking metrics, prototyping, testing, integration of existing models, creation of new models, data collection, analysis, debugging)
• Stay up to date with the latest research in document classification, text recognition and information extraction
• Set direction and identify opportunities to push boundaries of recognition
• Mentoring team members on code quality and engineering practices

Who you are 

You are a senior ML engineer who is passionate about building, shipping, and improving machine learning-powered systems. You have a proven track record of delivering state-of-the-art computer vision systems both on-device and on cloud and firsthand experience bringing them from the prototyping stage to production.

You recognize that software development encompasses both technology and human interaction and feel comfortable working independently or on a team. While you stay on top of the state-of-the-art in CV/ML, you value proven technologies and small increments. You are creative and determined to solve real-world problems by thinking outside the box and making an impact. You thrive on tackling open problems, taking ownership, and effectively overcoming obstacles. You pay attention to details and at the same time are able to take pragmatic shortcuts to reach our goals.

In particular, we are excited to hear from you if the following sounds like you:

• 5+ years of experience solving recognition problems in the industry with a proven track record of launched products
• Fluency in C++ and Python
• Running ML models on mobile devices
• Experience with relevant machine learning frameworks (Pytorch, Jax, Tensorflow)
• Skilled in software design, problem-solving, and debugging
• Experience in computer vision systems extracting information from printed documents or experience with fine-tuning of vision-language models is a plus

What we offer

Here are just some of the reasons why people choose to build their career at Scandit: 

• A highly skilled team and a fun environment where you can put your enthusiasm for cutting-edge technologies to use
• Hackathons 
• Flexible, office, hybrid or home working
• People-first culture
• Global team outings 
• Festive/end of year all company celebrations 
• Your birthday off 
• An attractive individual equity plan in a growth company 
• We are certified as a “Great Place to Work” in 7 countries!
• Excellent office infrastructure, optimized for hybrid working in Zurich, Warsaw, Tampere, and London
• Excellent support for remote work across Switzerland, Finland, Poland, UK, Italy and Germany
• Specific benefits related to the location you are joining

Who We Are

Scandit enables enterprises and consumers to change the way they interact with everyday objects and augment the physical world with real-time data captured by scanning barcodes and recognizing text, objects, and other visual identifiers using smartphones, tablets, wearables, drones and robots.

Scandit’s mobile data capture platform is built on proprietary computer vision, augmented reality, and machine learning technologies. Companies in industries such as retail, transportation & logistics, manufacturing, and healthcare can use Scandit’s technology to create and power mobile apps for crucial enterprise workflows like mobile point of sale, mobile shopping, self-checkout, inventory management, and proof of delivery.

Many of the world’s most innovative and successful companies are benefiting from Scandit’s enterprise-grade mobile data capture platform, including Sephora, Nissan, DHL, and Levi Strauss & Co.

Scandit was founded by a group of researchers from ETH Zurich and MIT. The company is headquartered in Zurich and is also represented in Boston, London, Warsaw, Tokyo and Tampere. Over the years, our company has evolved into a world-class team of mobile image processing, cloud-computing and “Internet of Things” experts from around the globe and has most recently also opened an office in Tampere, Finland.

“Everybody is welcome here” - Is a celebrated component of our DNA.

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

#LI-MB1

#engineering

The Role

The Lead Researcher in Quantum Machine Learning will be a member of Terra Quantum's AI Applied Research team. This team is at the forefront of conducting both fundamental and applied research in the field of quantum machine learning. Although the Lead Researcher will focus on innovating in quantum machine learning, the role involves translating research findings into practical algorithmic software solutions. The Lead Researcher is expected to closely monitor and analyse scientific and industrial trends and needs across short-term, mid-term, and long-term horizons, specifically within the quantum technology and machine learning sectors, to guide the development and implementation of hybrid quantum-classical algorithms.

Reporting directly to the Director of AI, the Lead Researcher in Quantum Machine Learning plays a pivotal role in driving excellence within their team. They are not only detail-oriented but also possess a remarkable capacity for enthusiasm. By demonstrating commitment and passion for the mission, they inspire their team members to contribute to making quantum technologies widely accessible and to effect positive change globally.

The Responsibilities

The Lead Applied Researcher should expect to work in the following Quantum Machine Learning Team activities.

• Fundamental research in quantum machine learning
  • Developing quantum machine learning algorithms for different data processing tasks, e.g. time series, routing and planning, image, graph data, or natural language processing
  • Keeping up with state-of-the-art approaches in quantum machine learning
  • Analysing parametrised quantum circuits in their capacity to learn via a hybrid quantum-classical optimization loop
  • Utilizing metrics of, e.g., the Fisher information matrix, the effective dimension, and Fourier terms accessibility for parametrized quantum circuit ansatz analysis
  • Improving the trainability of parametrised quantum circuits through layerwise batch-entropy regularization and similar techniques
  • Interpreting and explaining quantum machine learning models. Analysing the flow of information through different architectures of quantum neural networks
  • Researching and understanding where the quantum brings the benefit to machine learning
  • Developing data encoding and data processing techniques for different types of quantum computers
  • Assisting in writing patent draft applications
  • Writing research papers for scientific journals

• Efficient implementation of quantum machine learning algorithms
  • Executing quantum machine learning algorithms on QPUs, e.g. of QuEra, IonQ, Rigetti, and IBM Q
  • Adjusting and improving implementation of hybrid quantum neural networks for different QPUs
  • Exploring and testing the best ways to hybridize classical machine learning solutions with quantum machine learning
  • Understanding the way to implement an efficient interaction of hardware (CPU, GPU) and software (PyTorch, Pennylane)
  • Assisting in the development of our quantum machine learning SDK
  • Optimising, at least theoretically, the code of hybrid quantum-classical machine learning solutions for faster execution

• Supporting industry projects implementation
  • Bringing in novel ideas based on industry needs in time-series, routing and planning, GenAI, and natural language processing tasks
  • Brainstorming on possibilities of quantum machine learning algorithms applications to our client’s industry problems
  • Working on finding a theoretical or empirical advantage of using hybrid quantum-classical machine learning in industrial problems
  • Assisting in writing applied industry research papers for scientific journals

The Requirements

The Lead Applied Researcher is expected to have several qualifications depending on the area of activity in quantum machine learning.

• PhD in computer science, physics, mathematics, electrical engineering, or equivalent subject is required
• Publication record in quantum machine learning, or variational quantum algorithms is required
• Advanced expertise in one or more quantum programming languages (Qiskit, Q#, Pennylane, Cirq, Quipper, Scaffold, tket) is required
• Advanced experience working with variational quantum algorithms for machine learning is required
• Experience working with the classical machine learning algorithms is required
• Computational learning theory expertise is optional
• Expert knowledge in Python is optional
• Expert knowledge in Pytorch and TensorFlow is optional
• Experience in programming for GPUs is optional
• Experience in working with QPUs is optional
• Goal-oriented, analytical and the ability to work independently
• Flexible, proactive, and creative with the ability to work in the team
• Highly motivated and resilient with the ability to work interdisciplinary
• Proficiency in written and spoken English
• Applicants must have the legal right to live and work in the European Union or Switzerland. Unfortunately, we are unable to offer visa sponsorship for this role.

The Role

The Researcher in Quantum Machine Learning or Quantum Information will be a member of Terra Quantum's AI Applied Research team. This team is at the forefront of conducting both fundamental and applied research in the field of quantum machine learning. Although the Researcher will focus on innovating in quantum machine learning, the role involves translating research findings into practical algorithmic software solutions. The Researcher is expected to closely monitor and analyse scientific and industrial trends and needs across short-term, mid-term, and long-term horizons, specifically within the quantum technology and machine learning sectors, to guide the development and implementation of hybrid quantum-classical algorithms.

The Researcher in Quantum Machine Learning plays a role in driving excellence within their team. They are not only detail-oriented but also possess a remarkable capacity for enthusiasm. By demonstrating commitment and passion for the mission, they inspire their team members to contribute to making quantum technologies widely accessible and to effect positive change globally.

The Responsibilities

The Applied Researcher should expect to work in one and supporting in the other areas of the following Quantum Machine Learning Team activities.

• Fundamental research in quantum machine learning
  • Developing quantum machine learning algorithms for different data processing tasks, e.g. time series, routing and planning, image, graph data, or natural language processing
  • Exploring state-of-the-art approaches in quantum machine learning
  • Analysing parametrised quantum circuits in their capacity to learn via a hybrid quantum-classical optimization loop
  • Utilizing metrics of, e.g., the Fisher information matrix, the effective dimension, and Fourier terms accessibility for parametrized quantum circuit ansatz analysis
  • Improving the trainability of parametrised quantum circuits through layerwise batch-entropy regularization and similar techniques
  • Interpreting and explaining quantum machine learning models. Analysing the flow of information through different architectures of quantum neural networks
  • Researching and understanding where the quantum brings the benefit to machine learning
  • Developing data encoding and data processing techniques for different types of quantum computers
  • Writing research papers for scientific journals

• Efficient implementation of quantum machine learning algorithms
  • Executing quantum machine learning algorithms on QPUs, e.g. of QuEra, IonQ, Rigetti, and IBM Q
  • Adjusting and improving implementation of hybrid quantum neural networks for different QPUs
  • Exploring and testing the best ways to hybridize classical machine learning solutions with quantum machine learning
  • Understanding the way to implement an efficient interaction of hardware (CPU, GPU) and software (PyTorch, Pennylane)
  • Assisting in the development of our quantum machine learning SDK
  • Optimising, at least theoretically, the code of hybrid quantum-classical machine learning solutions for faster execution

• Supporting industry projects implementation
  • Bringing in novel ideas based on industry needs in time-series, routing and planning, GenAI, and natural language processing tasks
  • Brainstorming on possibilities of quantum machine learning algorithms applications to our client’s industry problems
  • Working on finding a theoretical or empirical advantage of using hybrid quantum-classical machine learning in industrial problems
  • Assisting in writing applied industry research papers for scientific journals

The Requirements

The Applied Researcher is expected to have several qualifications depending on the area of activity in quantum machine learning or quantum information.

• Currently pursuing or recently completed a degree in computer science, physics, mathematics,
  or equivalent subject
• Experience in one or more quantum programming languages (Qiskit, Pennylane, Cirq, etc.)
• Experience working with variational quantum algorithms for machine learning
• Experience working with classical machine learning algorithms
• Basic knowledge in Python, Pytorch and TensorFlow
• Experience in working with QPUs is optional
• Familiarity with quantum information theory is optional
• Familiarity with Tensor-Network techniques is optional
• Goal-oriented, analytical and the ability to work independently
• Flexible, proactive, and creative with the ability to work in the team
• Highly motivated and resilient with the ability to work interdisciplinary
• Proficiency in written and spoken English
• Applicants must have the legal right to live and work in the European Union or Switzerland. Unfortunately, we are unable to offer visa sponsorship for this role.

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 QRT’s 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. 

Your future role within QRT:

We are seeking a Market Microstructure Researcher to help optimize exchange connectivity and interaction for our high-frequency trading strategies. You will analyse network and exchange protocols, automate performance metrics, and lead experiments to improve our trading operations, with a focus on latency-sensitive exchanges.

• Network & Protocol Analysis: Analyse network and exchange protocol captures to identify inefficiencies and improve communication performance
• Exchange Research & Liaison: Research exchange features, attend presentations, and communicate with exchange counterparts to gather insights
• Execution Optimization: Reverse-engineer trading systems and design and conduct experiments to improve fill rates
• Cross-team Communication: Collaborate directly with trading and research teams to ensure best application of findings and direct PnL impact
• Data Analysis: Effectively work with large and robust datasets to identify and resolve inefficiencies in internal execution systems and exchange communication

Your present skillset:

• Degree in Computer Science, Engineering, or a related field
• 5+ years of experience in data analysis and/or low-level systems and network engineering
• Strong skills in Python and time-series analysis
• Understanding of network protocols such as TCP/IP and Ethernet
• Familiarity with market microstructure and low-latency trading is a plus
• Advanced networking and GNU/Linux knowledge is a plus

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. 

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 QRT’s 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.

Your future role within QRT

• A key member of the QRT Crypto desk, building and enhancing the quant technology stack for our systematic trading
• Building the front-office systems for algorithmic trading, across data, risk, live trading, post-trade, and infrastructure
• Working with traders and quants to roll-out, support and automate 24/7 trading strategies
• Integrating with DeFi venues, including onboarding real-time on-chain data feeds
• Working on greenfield projects as well as QRT's existing sophisticated tech stack
• Mentoring junior members of the team and helping to set high quality standards for code

Your present skillset

• 3-10 years’ professional experience
• Strong C++ experience, Python skills would be a plus
• Background in systematic trading advantageous
• Passionate about crypto and DeFi
• Very high standards in code quality and good development practices
• Knowledge of real-time, robust, scalable and quantitative applications
• Ability to architect high-throughput end-to-end systems
• Strong team-player and communication skills
• Experience with DevOps, CICD, AWS advantageous

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.

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 QRT’s 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.

Your future role within QRT

• Your core objective is to create high quality predictive signals.
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities.
• Share and discuss research results, methodology, data sets and processes with other researchers.
• Implement the signals and the relevant datasets within the global execution platform.
• Monitor signal behaviour and model performance over time.
• You would lead the full strategy research cycle from signal generation to implementation.

Your present skillset

• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering.
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus.
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail.
• Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#).
• Experience in exploring large datasets across multiple time frames is a plus.
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields.
• Capacity to work with autonomy within a collegial and collaborative environment.
• Strong capacity to communicate with technologists, data scientists and traders across the globe.
• Proven track record in delivering successful systematic strategies.

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.

At Inceptive, you will drive forward development that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software.

The design space of biomolecules is unimaginably vast — far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions.

We advance the state of the art in molecular design by training large-scale foundation models and developing cutting edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding.

You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs.

Your Mission, should you choose to accept it

• Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise
• Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design
• Analyze, visualize, and communicate results to support team efforts in improving models and data
• Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production
• Work with biologists to collect data for the training and evaluation of generative models of biomolecules
• Provide mentorship and technical direction to team members as appropriate

Qualifications

• 3+ years of hands-on experience developing ML models
• Demonstrated track record of implementing, training, improving advanced machine learning models
• Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework
• Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET
• Readiness to travel several times a year for company retreats and business events
• We value the benefits of in-person collaboration and expect candidates to primarily work from our office locations

Preferred technical skills

• PhD in AI/ML, computer science, computational biology, physics, or a related field, or equivalent practical experience (e.g., industry experience, research, or advanced technical expertise)
• Strong skills in designing, executing, and documenting machine learning experiments
• Practical experience with modern generative models
• Strong software engineering skills, in particular for data processing, evaluation of ML models, compute cluster orchestration
• Experience with large-scale model training, foundation models, model parallelism, multi-node training
• Experience with bio sequence data and datasets — various genomic and protein data, sequencing, functional assays, etc
• Knowledge of biochemistry, molecular/cell biology, and drug development

Compensation

$200K – $275K + Bonus + Equity

Role

As a Senior Research Scientist in the Applied Research team, you conduct applied research and design innovative algorithms in the space of geometric computer vision and image/video/vision-centric foundation models for deployment in industrial robotics at scale. In this role you define processes and develop approaches in Deep Learning that mitigate the risks of hallucinations, improve accuracy and deploy algorithms on industrial robotics workcells to gauge sim-to-real transfer of models. As a Senior Research Scientist at Intrinsic you provide input and guidance for the development and generation of synthetic data and annotations required for training foundation models at scale based on the identification of gaps in the sim-to-real transfer of models. You also work with Research partners and cross-disciplinary engineering teams to ideate new approaches and architectures to bring state of the art foundation models to real-world industrial applications. Constant learning and exploration of unfamiliar technologies is also part of this role. 

How your work moves the mission forward

Your work can play a significant role in democratizing access to advanced AI skills to the average user in robotics and enhance the credibility of deploying AI models at scale in industrial settings. As part of your day-to-day work: 

• You are insightful and innovative, proactively identifying needs and bottlenecks based on customer problems and proposing practical solutions that are deployable in high throughput environments.
• You serve as the nexus between the robotics team and our research partners—collaborating with them, providing engineering insights into research projects, and ideating practical next generation solutions. 
• You serve as an advisor to the engineering and other cross-functional teams providing critical guidance in terms of translating early (AI-powered) research capabilities into robust engineering capabilities in Flowstate (Intrinsic’s software platform for robotics solutions).
• You continually keep abreast of the latest developments in deep learning, AI, machine learning, perception to ensure that Intrinsic can continually keep evolving its advanced capabilities over time.
• Document and develop the prototype fully so it can be shipped to external users. 

In all the above, you will work closely with a sub-team within the R&D division, but will also frequently collaborate with other engineering, and product groups within Intrinsic.

Skills you will need to be successful

• Master’s or PhD degree in Computer Science, Robotics, or a related technical field with a high degree of passion for robotics and foundation models and a strong inclination towards accelerating the deployment of such models in practical industrial manufacturing applications.
• 3 years of experience in robotics software development or research (work on your PhD can count towards this).
• Proficiency programming in Python and at least one of the ML/DL frameworks such as PyTorch, Jax, and/or Tensorflow.
• Knowledge of robotics perception or manipulation algorithms.
• Experience working with robot hardware or simulation environments.
• A team player with a product mindset, a willingness to learn, and apply oneself to delivering value in practical real-world problems.

Skills that will differentiate your candidacy

• Advanced degree (Master's or PhD) in Robotics, Computer Science, or a related technical field.
• Expertise in deep learning, including transformer-based approaches for robotics, and other areas such as Learning from Demonstrations, Reinforcement learning.
• Proven ability to apply robotics ML/AI research to real-world problems and demonstrate tangible impact.
• Experience generating or utilizing synthetic data for machine learning in robotics.
• Publications in relevant robotics conferences or journals.

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

The Agentic Red Team is a specialized, high-velocity unit within Google DeepMind Security. Our mission is to close the "Agentic Launch Gap"—the critical window where novel AI capabilities outpace traditional security reviews. Unlike traditional red teams that hand off reports and move on, we operate with extreme agility, embedding directly with product teams as both a consulting partner and an exploitation arm. We act as a "special forces" unit capable of jumping into high-priority launches, relying on Google Core for foundational system-level protections so we can focus exclusively on model and agent-layer risks.

The Role

As a Senior Security Engineer on the Agentic Red Team, you will be the primary technical executor of our adversarial engagements. You will work "in the room" with product builders, identifying architectural flaws during the design phase long before formal reviews begin.

Your core focus will be to perform complex, multi-turn attacks on production-level AI models, specifically targeting agentic behaviors like tool usage and reasoning chains. You will not only find vulnerabilities but also help close the loop by contributing to "Auto Red Teaming" frameworks and defensive strategies, ensuring that your findings are codified into reusable guardrails for all Google agent developers.

Key responsibilities:

• Execute Agile Red Teaming: Conduct rapid, high-impact security assessments on agentic services, focusing on vulnerabilities unique to GenAI such as prompt injection, tool-use escalation, and autonomous lateral movement.
• Develop Advanced Exploits: Engineer and execute complex attack sequences that exploit non-deterministic model behaviors, agentic logic errors, and data poisoning vectors.
• Build Automated Defenses: Write code to transform manual vulnerability discoveries into automated regression testing frameworks ("Auto Red Teaming") that prevent regression in future model versions.
• Embed with Product Teams: Partner directly with developers during the design and build phases to provide immediate feedback, effectively shortening the feedback loop between offensive findings and defensive engineering.
• Curate Threat Intelligence: Maintain and expand a library of agent-specific attack patterns and exploit primitives to establish robust release criteria for new models.

About You

In order to set you up for success as a Software Engineer at Google DeepMind,  we look for the following skills and experience:

• Bachelor's degree in Computer Science, Information Security, or equivalent practical experience.
• Experience in Red Teaming, Offensive Security, or Adversarial Machine Learning.
• Strong coding skills in Python, Go, or C++ with experience building security tools or automation.
• Technical understanding of LLM architectures, agentic workflows (e.g., chain-of-thought reasoning), and common AI vulnerability classes.

In addition, the following would be an advantage: 

• Hands-on experience developing exploits for GenAI models (e.g., prompt injection, adversarial examples, training data extraction).
• Experience working in a consulting capacity with product teams or in a fast-paced "startup-like" environment.
• Familiarity with AI safety benchmarks, evaluation frameworks, and fuzzing techniques.
• Ability to translate complex probabilistic risks into actionable engineering fixes for developers.

The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

Our team, GeminiApp, is on a mission to build a universal AI assistant that will empower billions of people. We are creating a personal, proactive, and powerful life assistant that will be used multiple times a day to increase productivity and creativity by 10 to 100-fold. Our work is shaping how humanity interacts with AI at scale.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

As a Data Scientist on the GeminiApp team, you are a key partner and co-creator in our product strategy while managing a growing team. You will be instrumental in building a uniquely proactive and powerful assistant by ensuring our strategic decisions are grounded in data. This is a high-impact role for a data scientist who is excited about working in a fast-paced, innovative environment and who is passionate about building user-centered experiences that will redefine our relationship with technology.

Key responsibilities:

• Partner with Verticals PM, engineering, and UX to develop data-driven product strategies
• Translate ambiguous questions into well-defined problems, design experiments, and analyze large complex datasets for insights
• Develop and implement novel, goal-oriented metrics
• Build and deploy statistical/ML models to understand our users, enhance product capabilities and personalize user experience
• Communicate findings & recommendations to stakeholders, including executives
• Champion data-driven culture by feeding user engagement insights back into models
• Collaborate with the GenAI team on model quality and feature adoption
• Act as a technical leader for a global team, guiding junior members on complex analyses and upholding best practices to ensure high-quality, impactful work

About You

In order to set you up for success as a Data Scientist at DeepMind,  we look for the following skills and experience:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 years of experience with a Master's degree.
• 2 years of work experience identifying opportunities for business/product improvement and then defining/measuring the success of those initiatives.

In addition, the following would be an advantage: 

• A bias for action and a relentless drive to build something great. You are a resourceful and creative problem-solver, able to find innovative solutions in a fast-paced and dynamic environment. You are comfortable with ambiguity and thrive on a challenge.
• Strong business acumen and a strategic mindset. You have a proven ability to connect data-driven insights to business impact and can effectively translate business needs into data science problems.
• Deep technical expertise. You have a strong foundation in statistical modeling, machine learning, and experimental design. You are proficient in SQL and have hands-on experience with a programming language like Python or R.
• Exceptional communication and presentation skills. You can articulate complex technical concepts to both technical and non-technical audiences, including executive leadership. You are a compelling storyteller who can use data to influence decisions.
• A collaborative and influential partner. You have a track record of successfully collaborating with and influencing cross-functional teams, particularly engineering and product management, to drive data-informed decisions. You are ready to work in an environment with a shared roadmap that holds multiple teams accountable for both model quality and feature adoption.
• A commitment to user trust and privacy. You understand the importance of telling users what data is being used and why, and you are committed to providing users with granular, easy-to-understand controls over their personal information.

Application deadline: 12pm GMT 28th February 2026

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see ourApplicant and Candidate Privacy Policy.

At DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, maternity or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.