Experience Requirements:

• 3+ years

Benefits:

• Weekends Off

• Provident Fund

Experience Requirements:

• 0-1 Yr Exp

Experience Requirements:

• 2-4 years

Benefits:

• Flexible working hours

• Pet-friendly office

• Game room

• Stock purchase plan / Stock options

• Team building

Education Requirements:

• Ph.D. in Machine Learning / Artificial Intelligence, preferably on Generative AI / LLM topics

Experience Requirements:

• Experience in Machine Learning / Artificial Intelligence research, with a track record of publishing research papers and turning them into useful tools.

• Expert proficiency in the Python AI stack, especially with PyTorch, Hugging Face and LLM frameworks.

• Strong skills in software engineering (use of Git, production-ready code.)

• Strong written & oral communication skills in English.

• Bonus 1: open-source contributions are highly valued. Bonus 2: knowledge of cybersecurity fundamentals and techniques is also a plus.

Other Requirements:

• We are hiring people located in France or willing to relocate.

Responsibilities:

• Develop production-ready tools for LLM evaluation & mitigation that can be integrated in our software platform

• Conduct our scientific watch, reading academic papers in the fields of AI Testing / Benchmarking / Security.

• Communicate findings with other AI teams at customers & partners, such as Mistral AI, AWS, Google, Microsoft, NVIDIA, in the form of presentations and papers.

• Push the frontier of AI Safety & Security research with a focus on tools for real-life applications.

Benefits:

• Unlimited vacation

• Flexible working hours

• Remote work possible

Responsibilities:

• Connect our technology with customer needs

• Derive insights and strategic suggestions based on customer data

• Design and build data-based consulting services

• Conduct modeling using our AutoML solution DAVinCI LABS

• Provide training on how to use the solution and lectures on machine learning theory

Education Requirements:

• PhD

Experience Requirements:

• Several years of relevant professional experience.

• Proven excellence in teaching foundational computer science subjects.

Other Requirements:

• Strong proficiency in both written and spoken German (C2) and English for course instruction.

• The application must include a detailed teaching concept that addresses specific ideas for improving teaching in the computer science degree programs at the University of Tübingen as well as new and innovative forms of teaching.

Responsibilities:

• Teaching 12 semester hours (SWS) per semester, including at least one large foundational course in Computer Science for the bachelor’s program at the University of Tübingen. This includes topics in technical computer science (e.g. digital technology, chip design, computer architectures, hardware/software codesign, parallel architectures, operating systems).

• Innovating and improving teaching through new formats and continual revision based on evaluations.

• Supporting Bachelor's and Master's courses in the field of computer engineering.

• Participation in collaborative research projects within the Tübingen AI Center.

• Conducting independent research and possibly leading third-party funded projects.

Benefits:

• Participation in the company’s employee share options plan

• 25 days holiday, plus bank holidays

• Flexible working from home policy plus a one-off WFH allowance when you join

• Work from outside of the UK for up to 6 months each year

• Enhanced parental leave 🚲 Bike2Work scheme 📚 Annual learning and development allowance [👨‍👩‍👧](https://emojipedia.org/family-man-woman-girl/) Company-funded fertility and family-forming programmes [🌸](https://emojipedia.org/cherry-blossom/) Menopause care programme with Maven 🏥 Private healthcare and dental cover, discounts on gym members and relaxation apps, and access to a range of mental health programs

Education Requirements:

• A degree in Computer Science, Machine Learning, or a related field, or equivalent industry experience

Experience Requirements:

• 3+ years of experience working with deep learning and statistical models

Responsibilities:

• Train models and conduct experiments to assess model performance in live deployments

• Work on experimental model architectures, exploring multimodal, efficient long-context etc.

• Develop post-training strategies to achieve state of the art performance on domain-specific tasks

• Generate, collect, and annotate contact center data from sources such as real customer calls, chats, online open datasets, and synthetic data

• Develop robust evaluation benchmarks to track improvements in production models Collaborate with the legal and compliance team to address any compliance or data privacy-related issues Work closely with product and engineering teams to ensure alignment with business and production goals Stay informed about the latest advancements in machine learning, ASR, TTS, and LLM to continuously enhance our technologies

Benefits:

• Competitive Salary Offering

• Company Equity Package

Benefits:

• Limitless growth opportunities

• Shape your career

• Explore your passions

• Generous PTO

• Fitness benefits

Benefits:

• Remote-First Culture

• Cutting-Edge Technology

• Growth Opportunities

• Team Collaboration

• Mission-Driven Work

Benefits:

• Remote-First Culture

• Cutting-Edge Technology

• Growth Opportunities

• Team Collaboration

• Mission-Driven Work

Education Requirements:

• Thorough understanding of Machine Learning fundamentals

Experience Requirements:

• Experience building deep-net models

• Experience with PyTorch or TensorFlow

• Excellent problem-solving ability

Responsibilities:

• Own the end-to-end solution to automate workflows involving intelligent document processing

• Research and develop the right ML/AI models to solve business problems

• Implement solutions and guide the deployment

• Guide the data engineering team on collecting training data

• Guide development of exception handling to provide an end-to-end solution integrating actively labeled data in real-time evolving models to achieve state-of-the-art precision

Education Requirements:

• Minimum Doctoral degree or in the last year of the Doctoral degree in Mathematics/Statistics, Computer Science, Physics or Electrical Engineering.

Other Requirements:

• Demonstrable capacity to produce high quality peer reviewed research.

• Familiar with Linux infrastructure and python (C++ familiarity would be beneficial).

• Preferably some knowledge of financial market mechanics.

• Approachable attitude to joint work and peer review and ability to present complex ideas in a concise manner.

• No previous experience is required.

• mathematics hobbyists

Benefits:

• Rich innovative software stack, freedom to choose the best suitable technologies.

• Remote-first ideology: freedom to operate from the home office or any suitable coworking.

• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.

• Regular performance and compensation reviews.

• Recurrent 1-1s and measurable OKRs. In-depth onboarding with a clear success track. Competera covers 70% of your training/course fee. - 20 vacation days, 15 days off, and up to one week of paid Christmas holidays. - 20 business days of sick leave. - Partial medical insurance coverage.

Experience Requirements:

• A minimum of 5 years of experience in data science or a related field.

• At least 3 years of experience working with tabular and mixed (multimodal) data (e.g., tabular data combined with text, audio, or images).

Other Requirements:

• Proficiency in SQL for data manipulation and extraction.

• Strong Python skills, capable of writing modular and readable code for experiments and prototypes.

• A solid mathematical background, preferably in a Computer Science-related field.

• Proficiency in the scientific Python toolkit, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.

• Familiarity with Time Series Forecasting approaches.

• Experience in statistical testing methodologies, including A/B testing.

• Upper-intermediate or higher level of English (for future communication with clients and user interviews)

Responsibilities:

• Be responsible for DS-ML-related solutions developed by all Service and Delivery(SnD) squads: maintenance and improvement of existing solutions; design, development, and implementation of new solutions.

• Provide technical leadership for other SnD DSs.

• Test developed algorithms, work with the SnD team within UAT, adapt, and reach DOD and DOR.

• Verify key tasks done by SnD DS, such as model training and AB test design.

• Conduct code reviews for DS-ML-related solutions. Automate DS work in SnD.Develop data requirements for SnD implementation projects.

Benefits:

• equity in a fast-moving, profitable startup

Education Requirements:

• PhD

Other Requirements:

• Strong software development skills

• Excitement to change the world with AI products

• US citizenship, and eligibility to obtain TS/SAP clearance

• Desire to work with the world's leading experts in a fast-moving environment

Education Requirements:

• Completed a Master's degree in Computer Science, Mathematics, or a related field, with a published paper in a respectable journal or conference.

Experience Requirements:

• at least 3 years of experience working with computer vision models.

Responsibilities:

• Develop your SOTA: Our team is a pioneer in adversarial AI research with numerous studies under our belt. We will guide your research, development, and implementation of state-of-the-art (SOTA) models and techniques.

• Research and Development: Conduct research on adversarial attack and defense techniques for computer vision models. Explore state-of-the-art methods and propose innovative solutions.

• Collaboration: Work closely with team members, participate in brainstorming sessions, and contribute to the team's success.

• Generative Vision: You will help with the research and development of new generative vision pipelines, tackling various modalities and challenges.

Experience Requirements:

• 3+ years of hands-on experience in Computer Vision and deep learning, particularly in object detection and image classification.

Responsibilities:

• Lead Computer Vision Initiatives: Develop and deploy advanced computer vision models for tasks such as object detection, image classification, data extraction, and image quality assessment.

• Drive Innovation in Core-ML Projects: Work on critical machine learning projects, including Credit Risk Modeling and Scorecard Development, ensuring robust and scalable solutions.

• Data Exploration and Analysis: Explore and analyse unstructured data, particularly images, using advanced image processing techniques.

• Model Research and Development: Collaborate with the data science team to research, develop, evaluate, and optimise deep learning models tailored to solve specific business problems.

Benefits:

• Full insurance benefits including medical, dental, vision, and life insurance for you and your dependants

• 401k plan with employer matching

• Flexible PTO and employees are encouraged to take time off to recharge

• Flexible working hours

• Parental leave

Education Requirements:

• PhD or equivalent research experience

Other Requirements:

• Strong background in CV, ML, AI, computer science, engineering or related fields

• Track record of applied research in computer vision

Responsibilities:

• Research and develop algorithms for computer vision-based problems including scene understanding and anomaly detection

• Develop performance and quality metrics for ML models and systems

• Collaborate with software engineers and product owners on system architecture, design and production code, especially where ML models are used

• Keep up to date with state of the art in ML and CV

• Mentor younger scientists