AI Jobs

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:

• 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

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.

Benefits:

• Healthcare

• Remote Work

• Integrated Team

• Unlimited Time Off

• A Voice, Professional Development

Benefits:

• 100% paid comprehensive medical coverage, including vision and dental, and HSA plan options for employees and their dependents

• Health & wellness app reimbursement

• On-site gym

• Free lunch

• 12 company holidays and flexible time off Generous parental leave: 18 weeks for birth parents and 12 weeks for non-birth parents Hybrid work environment: 3 days a week onsite and two days work from home Twice yearly multi-day offsites Safe harbor matching 401(k) Tax Advantaged Accounts including FSA, Dependent Care FSA, HSA, and commuter benefits Employer Paid Basic Life & AD&D Short Term and Long Term Disability

Education Requirements:

• PhD in biological sciences

Experience Requirements:

• at least 5-year experience in RNA-targeted small molecule discovery

• Proven hands-on experience in working with RNA targets and related screening technologies including but not limited to ASMS, ALIS, Microarray, SPR, ITC.

• Ability to evaluate newer methods as appropriate and implement novel approaches to screen RNA as needed.

• Ability to independently drive, manage, execute, and deliver results on key programs under tight timelines.

• Ability to work in a collaborative environment to enable integration of state-of-the-art technology platform with RNA biology to accelerate the program pipeline.

Responsibilities:

• Work with company leadership to advance our strategy for targeting RNA with small molecules and RNA degraders.

• Develop RNA screening strategy, establish screening platform and relevant technologies internally and/or in collaboration with external partners including but not limited to ASMS, Microarray, SPR, ITC, and/or other relevant biophysical methods. In addition, evaluate any new methods and implement them as necessary.

• Enable RNA-directed small molecule drug discovery efforts. Establish validated processes for small molecule hit ID, validation, and lead optimization for RNA targets. Deliver on program requirements in a timely manner.

• Collaborate with the drug discovery, ML data and ML teams to build an integrated workflow to support RNA biology programs.

• Provide scientific leadership and perform day-to-day lab activities.

Experience Requirements:

• 1+ years

Experience Requirements:

• 3+ years

Experience Requirements:

• 3+ years

Education Requirements:

• BS, MS, PhD in quantitative field, such as Physics, Mathematics, Statistics, Engineering, or equivalent practical experience.

Experience Requirements:

• Experience with some form of Deep Learning, for example Image recognition, or NLP, and a solid understanding of the foundations.

• Experience with programming in Python.

• Good knowledge of statistics, data analysis, and modelling methods.

• Problem solving skills with respect to approaching a new dataset/customer request and formulating a problem.

Other Requirements:

• Good written and verbal communication.

• Demonstrated ability to work with minimal to no supervision.

• Ability to work remotely with cross-cultural teams.

• Self-motivation to learn new concepts and an excellent record of execution.

• A sense of urgency, result orientedness, and excellent ability to prioritize.

Responsibilities:

• The data scientist in a team has a varied role. This can include working directly with our customers to support the deployment of our products, or internally to strengthen the products themselves.

• For our customers, your work will vary from initial data exploration, to modelling and problem formation, and then finally to the Reinforcement Learning training itself.

• Subspecialties within this broad scope are encouraged.

• You will work collaboratively with our backend, product, and AI teams.