NumPy Jobs in Hungary.
All active NumPy roles based in Hungary.
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Senior Python Developer
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Company Overview
Interactive Brokers Group, Inc. (Nasdaq: IBKR) is a global financial services company headquartered in Greenwich, CT, USA, with offices in over 15 countries. We have been at the forefront of financial innovation for over four decades, known for our cutting-edge technology and client commitment.
IBKR affiliates provide global electronic brokerage services around the clock on stocks, options, futures, currencies, bonds, and funds to clients in over 200 countries and territories. We serve individual investors and institutions, including financial advisors, hedge funds and introducing brokers. Our advanced technology, competitive pricing, and global market help our clients to make the most of their investments.
Barron's has recognized Interactive Brokers as the #1 online broker for six consecutive years. Join our dynamic, multi-national team and be a part of a company that simplifies and enhances financial opportunities using state-of-the-art technology.
What will be your responsibilities within IBKR:
Technical Excellence
- Design, optimize, and extend transaction surveillance and data pipeline processes to enhance system efficiency, reliability, and scalability
- Navigate seamlessly between strategic, system-level architecture and function-level implementation details of our surveillance system, which orchestrates 150+ processes
- Optimize data architectures and databases for maximum performance and reliability
- Build developer tooling to accelerate development workflows and system monitoring
- Ensure data accuracy, security, and compliance with regulatory standards
Ownership and Cross-Functional Partnership
- Take ownership of projects and sub-systems from planning through resolution, making impactful decisions on complex technical and business-related questions
- Collaborate effectively with quantitative engineers, surveillance model developers, and Compliance stakeholders to translate complex business requirements into scalable designs and processes
- Identify project bottlenecks, risks, and limitations; calculate costs; and provide strategic insights to stakeholders
- Transform high-level surveillance concepts into production-ready processes that deliver actionable insights
Data Architecture & Stewardship
- Own and curate dozens of mission-critical datasets that drive surveillance operations
- Design, build, and automate robust data pipelines to support real-time and batch processing
- Develop advanced data quality frameworks to proactively identify issues before they impact operations
Innovation & Optimization
- Contribute to the evolution of coding standards and internal code review processes
- Drive best practices in data storage, retrieval, governance, and privacy protection
- Drive automation of processes and workflows to reduce manual effort and enhance system maintainability
Which skills are required:
- 5+ years of professional software engineering experience in Python, C++ or Java
- 3+ years of professional experience in Python as a primary language (non-scripting)
- Extensive experience in Pandas or NumPy, Polars is nice to have
- 1-3 years of professional experience with Linux operating systems
- Thorough understanding of databases and SQL
- Experience with large Python codebases
- Bachelor's or master's degree in Computer Science, or a related area
- High attention to detail
Good to Have:
- Experience with data engineering or ETL pipelines
- Knowledge of finance
- Knowledge of C++ or Java
- Masters/PhD
To be successful in this position, you will have the following:
- Self-motivated and able to handle tasks with minimal supervision.
- Superb analytical and problem-solving skills.
- Excellent collaboration and communication (Verbal and written) skills.
- Outstanding organizational and time management skills.
Company Benefits & Perks
- Discretionary annual bonus (cash and stock)
- Private healthcare insurance
- Subsidized recreational pass (AYCM XL package - 80% employer contribution)
- Daily food allowance in the office
- Monthly BKK pass
- Hybrid way of working (1 day home office/week)
- Modern office in the heart of Budapest with free amenities
- Great atmosphere with friendly and exceptional colleagues, frequent company outings.
*The benefits package will be reviewed regularly and may be subject to change.
Ready to apply?
Apply to Interactive Brokers
Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
Senior Applied Scientist
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Here’s a summary of the role:
You’ll use your applied machine learning and generative AI skills to design and ship LLM powered product experiences that solve real problems for real users. You turn messy documents and complex language into smart assistants, agentic solutions, and search experiences that feel fast, reliable, and trustworthy.
In this role you work end-to-end: framing problems, shaping prompts and workflows, orchestrating tools and retrieval, and partnering with engineers and product managers to bring modern AI into production. If you enjoy building with large language models and care deeply about evaluation, safety, and impact, you’ll feel at home here.
Here’s a breakdown of what you’ll do (not all of it, just the important stuff):
- Design, prototype, and refine LLM based features over large document sets.
- Orchestrate multistep, agentic workflows and tool calling (including MCP servers and other integrations) so LLMs can take meaningful actions, not just generate text.
- Define evaluation frameworks, experiments, and metrics so you can measure model quality, relevance, and safety with confidence.
- Use AWS services (i.e. AWS Bedrock) to deliver reliable, secure, and scalable AI capabilities.
- Work closely with domain experts, PMs and software engineers to turn prototypes into reliable, production ready services.
- Handle complex, domain specific text (e.g. legal, financial, or regulatory content) with a strong focus on accuracy, robustness, and privacy.
- Communicate your findings clearly, share best practices, and stay up to date with the latest ML and AI research that can improve your solutions.
These are the essentials you’ll need to get an interview:
- Hands-on experience building LLM powered applications or features (for example RAG systems, chatbots, assistants, agentic solutions or document centric workflows) — not just using chat interfaces.
- Strong Python skills and everyday comfort with the modern data / AI ecosystem (e.g. pandas, NumPy, basic ML libraries, HTTP APIs, and SDKs for cloud AI services).
- Practical experience with LLM powered solution design, evaluation, and iteration: you know how to test, compare approaches, and choose the one that works best with real data.
- Familiarity with at least one cloud platform (ideally AWS) and building or contributing to services or pipelines that run in production.
- A degree in Computer Science, Data/Applied Science, Mathematics, Statistics, or a related technical field, or equivalent practical experience.
- Clear communication skills, collaborative mindset, and a genuine interest in learning, sharing knowledge, and iterating quickly based on feedback.
It would be great if you had these to, but we’ll support you if you don’t:
- Experience designing and implementing agentic workflows (multistep reasoning, tool calling, planners) and/or building MCP servers or similar tool integrations.
- Hands-on experience with AWS Bedrock or comparable platforms (model selection, configuration, guardrails, evaluation, and cost/performance trade-offs).
- Experience with semantic search, vector databases, and information retrieval techniques in production systems.
- Familiarity with observability and evaluation for LLM applications (e.g. logging, feedback loops, offline and online evaluation, safety checks).
- Experience working with complex or regulated content such as legal, risk, compliance, financial, or governance documents.
#LI-Hybrid
About Us
Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 700,000 board members to clarify risk and elevate governance. The Diligent One Platform gives practitioners, the C-Suite and the board a consolidated view of their entire GRC practice so they can more effectively manage risk, build greater resilience and make better decisions, faster.
Learn more at diligent.com or follow us on LinkedIn and Facebook
What Diligent Offers You
- Creativity is ingrained in our culture. We are innovative collaborators by nature. We thrive in exploring how things can be differently both in our internal processes and to help our clients
- We care about our people. Diligent offers a flexible work environment, global days of service, comprehensive health benefits, meeting free days, generous time off policy and wellness programs to name a few
- We have teams all over the world. We may be headquartered in New York City, but we have office hubs in Washington D.C., Vancouver, London, Galway, Budapest, Munich, Bengaluru, Singapore, and Sydney.
- Diversity is important to us. Growing, maintaining and promoting a diverse team is a top priority for us. We foster and encourage diversity through our Employee Resource Groups and provide access to resources and education to support the education of our team, facilitate dialogue, and foster understanding.
Diligent created the modern governance movement. Our world-changing idea is to empower leaders with the technology, insights and connections they need to drive greater impact and accountability – to lead with purpose. Our employees are passionate, smart, and creative people who not only want to help build the software company of the future, but who want to make the world a more sustainable, equitable and better place.
Headquartered in New York, Diligent has offices in Washington D.C., London, Galway, Budapest, Vancouver, Bengaluru, Munich, Singapore and Sydney. To foster strong collaboration and connection, this role will follow a hybrid work model. If you are within a commuting distance to one of our Diligent office locations, you will be expected to work onsite at least 50% of the time. We believe that in-person engagement helps drive innovation, teamwork, and a strong sense of community.
We are a drug free workplace. Diligent is proud to be an equal opportunity employer. We do not discriminate based on race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, physical disability, mental disability, age, military status, protected veteran status, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information, or sexual orientation in accordance with applicable federal, state and local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Diligent's EEO Policy and Know Your Rights. We are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at recruitment@diligent.com.
To all recruitment agencies: Diligent does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, Diligent employees or any other organization location. Diligent is not responsible for any fees related to unsolicited resumes.
Ready to apply?
Apply to Diligent Corporation