Benefits:

• Health & Commuter Benefits

• Flexible PTO

Education Requirements:

• Degree within Computer Science, Data Engineering, or a related field.

Experience Requirements:

• 2-4+ years of industry experience in applying AI/ML, preferably on well-known consumer data products or services.

• Hands-on experience in delivering production-ready code (Python, Java, etc.)

• Hands-on experience using modern big data pipelines (AWS, Google Cloud, Snowflake)

• AI/ML models, Natural language process (NLP) and data mining experience

Other Requirements:

• Are you ready to work (hybrid) out of our downtown Manhattan office 3 days a week (Tuesday-Thursday)? (no relocation benefits)

• Do you require any form of visa sponsorship or immigration support? (Includes new or transfer H1, O1, PERM, F1-OPT, STEM extensions, etc.)

Responsibilities:

• Process, cleanse, and verify the integrity of data used for downstream analytics products

• Apply advanced machine learning, graph analytics, data mining, statistical methods, algorithms, and time series models to vast amounts of user data to derive insights based on the knowledge graph (ontology)

• Participate in strategic planning and be responsible for the team roadmap and its execution.

Responsibilities:

• Basic and applied research of AI algorithms (deep learning, etc.)

• Analysis, proposal, and verification using AI algorithms to solve business issues

• Engineering such as system development using AI algorithms

Education Requirements:

• Computer science, mathematics, statistics or a related degree;

• Master’s degree in machine learning, neural networks, deep learning or related fields;

Experience Requirements:

• Experience in image processing with OpenCV and Computer Vision

• Analytically way of meaning and understanding of mathematical models

• Working with mathematical packages as R package, Matlab or Octave

• CNN (Convolutional Neural Network), training Histogram Oriented Gradients object detectors

• Convolutional Neural Network object detectors, unsupervised and semi-supervised learning, sequence-to-sequence models based on recursive / recurrent neural networks.

Responsibilities:

• Specjalista ds. Analizy Danych odpowiadają za analizę, interpretację i wizualizację danych.

• Jego głównym zadaniem jest wydobywanie wartościowych informacji z danych, które mogą przyczynić się do poprawy jakości algorytmów ML oraz do osiągnięcia celów projektu, oraz implementacja zaawansowanych modeli statystycznych.

Education Requirements:

• Tertiary qualification in Geology or Earth Science.

Experience Requirements:

• Extensive experience experience in mineral resource evaluation (>20years), working in both open pit and underground mining environments.

Responsibilities:

• Lead an expanding resource geology team, providing expertise on resource evaluation methodologies, and ensure the quality control of all resource models and geometallurgical models.

• Audit the clients mineral resource (Kriging) models and Stratum’s generated models.

• Assist in the audit and analysis of complex mine site databases composed of varied geological and geochemical data to evaluate critical issues.

Experience Requirements:

• least 5-7 years of experience as a Senior Data Scientist

Experience Requirements:

• 3+ 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

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:

• 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:

• 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

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

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• 5+ years of experience doing quantitative analysis within a digital product environment.

Responsibilities:

• Enabling the rapid growth of our business; understanding the ecosystem of our business and identifying the highest impact areas for product-led growth.

• Defining key virality metrics and tracking KPIs to analyse what really matters. You’ll closely monitor our K-factor and find opportunities to improve it.

• Leading the measurement of ROI, incrementality, and cannibalisation of new viral initiatives.

• Influencing the roadmap of product teams through presentation of data-based recommendations.

• Applying graph theory and building network models to uncover new viral opportunities.

Experience Requirements:

• 5-7 years experience in NLP, Machine Learning, Deep Learning, Python, Computer Vision & 1-2 years exp in Gen AI.

Education Requirements:

• PhD in Remote Sensing, Environmental Science, Geospatial Science, or a related field.

Experience Requirements:

• Extensive experience with remote sensing techniques, particularly for flood detection and analysis.

• Proven expertise in change detection and workflow development for event mapping.

Other Requirements:

• Proficiency in using GIS and remote sensing software (e.g., ArcGIS, ERDAS IMAGINE) and programming languages (e.g., Python, R).

• Strong analytical skills and the ability to translate complex data into actionable insights for flood risk management.

Responsibilities:

• Lead the development and application of remote sensing methodologies for flood detection, change detection, and event mapping.

• Design workflows that enable efficient processing and analysis of satellite and aerial imagery for flood monitoring.

• Collaborate with data science and engineering teams to integrate flood detection models into our platform.

• Conduct research and develop algorithms to enhance the accuracy of flood event mapping and prediction.

• Provide technical expertise and guidance on flood-related risk assessment and management strategies.