Design and execute complex oncology experiments using molecular biology techniques, perform high-throughput drug screening, analyze data to inform research decisions, and develop laboratory protocols while ensuring effective resource management.

Title: Member of Research Staff (USA-remote) Location Remote, United States Employment Type Full time Department Research Job Description: Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. As a Member of Research Staff, you will work at the forefront of modern statistical machine learning. Your research colleagues have collectively published hundreds of academic articles in top-tier venues on machine learning, systems, and theory, and we meet regularly to stay current on the latest academic research and share ideas. Founded in 2007 by two leading scientists (see management bios), Voleon supports a culture of curiosity, collegiality, and creativity. Your work will focus on financial market prediction and portfolio optimization. The behavior of financial markets is noisy and violates a number of classical statistical assumptions, and we’ve spent over a decade pioneering scientific advances in the application of machine learning techniques to this domain. You will work with a complex and diverse array of datasets to implement and iterate on predictive models. Predicting financial markets is an enduringly hard problem, but results are immediate and unambiguous. Years of academic training has prepared you for this moment. You won’t just conduct research, you’ll apply it on a daily basis, working with a team across the entire life cycle of applied research problems. Your work will span from basic research to productizing solutions and validating their efficacy in live trading. This role is a means to make a difference: you will help direct billions of dollars in trades daily while making an enduring impact on our field. *** Relocation and work visa eligibility for qualified candidates*** Responsibilities - Develop a rich understanding of Voleon’s challenges and methodologies and propose research innovations and experiments to build, maintain and optimize the models that govern our investment strategy - Prepare and analyze new datasets to assess their predictive efficacy - Develop, validate, and implement new models into production - Design and conduct experiments to improve simulations and evaluate the success of new models in a live environment - Communicate and collaborate effectively with other Members of Research Staff and Software Engineers at each stage, driving progress towards tangible outcomes - Keep up to date on the latest academic research to identify novel approaches to explore for application to our domain Requirements - Background in modern statistical methods and machine learning with a track record as an applied researcher - Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement) - Interest in software development techniques and willingness to write production level code (Python and/or R preferred) - Ability to solve large-scale computing problems - Eagerness to work in collaborative and diverse teams - Interest in financial applications is essential, but prior finance industry experience is not a pre-requisite - Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred “Friends of Voleon” Candidate Referral Program If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program. Equal Opportunity Employer The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Role Description RBC is seeking to hire Sr. Software Development Engineer in Test (Sr. SDET) for RBC Caribbean technology for Core Banking and Specialized applications, who will be responsible for QE and automation processes, methodologies, and test strategy improvements. You will be accountable for driving quality by leveraging automation to improve quality through early defect detection. - Accountable for driving test automation framework development and automated test case creation and execution, maximizing automation for all project deliverables and common quality activities. - Responsible for developing and executing automated test plans for ecosystem/program/large projects (might assume planning execution accountability). - Accountable for driving quality and champion defect prevention/early defect detection. - Use AI driven testing approaches including intelligent test generation and predictive defect analysis. - Accountable for guiding a team of SDETs in Automation to provide the best support and automation for our test activities in projects/programs. - Create Test Suite, Traceability matrix etc. and provide support on test suite walkthrough with different teams. - Develop and maintain existing applications automation scripts for test activities and aligning to RBC Quality Engineering practices while partnering across IT and with assigned business lines to plan functional and non-functional testing activities. Qualifications - Computer Engineering, Computer Science or related (technical) degree / diploma. - 7+ years of proven experience in design and development of test automation infrastructure and automation scripts for large enterprises. - Deep technical knowledge of Python, JavaScript, Java, BDD, Playwright, Cucumber, RestAssured, Robot Framework, TestNG, Microservices and APIs, build tools such as Maven/Gradle and Source Code Management tool such as Git and GitHub. - Banking functionality knowledge. - Experience in test case design and automation at different levels (component/service/APIs, integration, mobile, end to end/user scenarios) and non-functional testing (performance testing, security testing). Requirements - Certified ISTQBE Test Automation Engineering (Nice-to-have). - Experience as a developer (Nice-to-have). - Experience in testing IBM iSeries Applications, Web Applications and File validations with proven knowledge of API and Database testing and test automation and rich experience in different types of testing (Nice-to-have). - Experience with cloud solutions such as ELK and Kafka and frameworks such as Spring (Nice-to-have). Benefits - A comprehensive Total Rewards Program including bonuses and flexible benefits. - Leaders who support your development through coaching and managing opportunities. - Ability to make a difference and lasting impact. - Work in a dynamic, collaborative, progressive, and high-performing team. - Opportunities to do challenging work. - Access to world-class training.

Role Description We are looking for a Research Engineer, Agentic Retrieval . You'll work at the seam between agent systems research and retrieval engineering, running a tight loop between hypothesis, experiment, and shipped artifact. - Chase questions about agent memory structure, re-querying versus reasoning, skill and tool retrieval, and defining success in multi-step trajectories. - Investigate how real agent stacks use Qdrant today and identify areas for improvement. - Maintain awareness of the fast-moving agent ecosystem. - Every cycle should produce actionable insights for the field, customers, or the company. What you will own - Define what good agentic retrieval looks like. - Characterize retrieval patterns inside real agent loops and develop a vocabulary for the team and field. - Treat agent memory as a systems problem, focusing on episodic, semantic, and procedural memory. - Investigate skill and tool retrieval as a first-class problem. - Design and run experiments on retrieval inside agent loops. - Build evaluation infrastructure for agentic retrieval. - Profile agent retrieval traces end to end. - Study how real agent stacks use Qdrant in production. - Pair with design-partner teams to incorporate real constraints into research priorities. - Influence the roadmap by translating evidence into product bets. Qualifications - You read and reason about LLM behavior directly. - You treat memory as a systems design problem. - You understand tool and skill systems as retrieval problems. - You have a working theory of context engineering. - You build evals before features. - You know vector search internals at a decent level. - You write precisely. Nice to have - Contributions to agent stacks, skill systems, MCP servers, RAG tooling, or eval harnesses. - Experience designing agent benchmarks or running them at scale. - Familiarity with Qdrant or comparable vector search systems under production agent traffic. - Track record working with design-partner customers or open-source community contributors. Benefits - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. - For US-based candidates, a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Company Description Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.