Education Requirements:

• Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field

Experience Requirements:

• 2 to 4 years of relevant experience in the field of analytics

Other Requirements:

• Analytical Skills, Data Analytics, and Data Modeling

• Strong communication skills, both written and verbal

• Experience in analyzing and interpreting complex data sets

• Proficiency in data visualization tools and techniques

• Attention to detail and problem-solving abilities

Responsibilities:

• performing day-to-day activities such as data analytics, data modeling, MIS, building dashboards and statistical analysis

• communicate findings and insights to stakeholders and collaborate with the AI team to develop comprehensive solutions

Education Requirements:

• Bachelor’s degree in computer science, Data Science, Statistics or related field

Other Requirements:

• Demonstrated interest in machine learning and artificial intelligence is essential

• Knowledge of statics and probability is a must

Responsibilities:

• Study and transform data science prototypes

• Select appropriate datasets and data representation methods

• Run machine learning tests and experiments

• Research and implement appropriate Machine Learning algorithms and tools

• Develop machine learning applications according to requirements

Benefits:

• Competitive compensation package

• Equity

• Employer-covered health/vision/dental insurance

• 401k matching

• Generous PTO allowance

Education Requirements:

• Strong CS, math, science or similar degree from a leading program

• PhD applicants actively considered

Other Requirements:

• Comfortable using scripting languages, and relational or NoSQL databases

• Familiar with general-purpose machine learning methods

• Passionate about using data to drive strategy and business recommendation

Responsibilities:

• Participating in envisioning, designing, coding, testing and improving algorithms

• Collaborating with software engineers and partner company stakeholders

• Identifying external datasets and developing API or other methods for accessing them

• Designing experiments to answer targeted questions

Benefits:

• 401(k) plans

• Comprehensive Healthcare and Dental Benefits

Education Requirements:

• Ph.D. or Bachelor's degree in a quantitative field such as Computer Science, Mathematics, or equivalent industry experience

Experience Requirements:

• 4+ years of experience working with AI/ML models, specifically in the fields of document understanding, computer vision, and multi-modal learning

• Proven expertise in training and evaluating models for complex document extraction

• Deep NLP Expertise

• OCR Integration

• Model Pretraining and Fine-tuning

Other Requirements:

• Solid programming skills in Python and proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch)

• Layout Analysis

• Benchmarking and Evaluation

• Vision-Language Models

Responsibilities:

• Design, train, and evaluate document understanding models for extracting complex data

• Develop and optimize multi-modal visual Q&A models

• Collaborate with the team to integrate AI-driven features into Tensorlake’s platform

• Work closely with users and customers to understand their needs

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Company share programme

• Hybrid and/or flexible work arrangements

• Core benefits of market leading private healthcare, life assurance, critical illness cover, income protection, alongside a company paid health cash plan (including gym discounts)

• A flexible £2,000 (pro-rata) benefits fund to spend on additional benefits of your choice, including tech scheme and cycle to work benefits

Education Requirements:

• Experience with Machine Learning in a research environment.

• Demonstrate proficiency in Python software development skills

• Experience with computer vision and robotics. More specifically object detection, tracking and localization.

• Solid software engineering design principles and up-to-date knowledge of Python best practices

• An ability to understand both technical and commercial requirements.

Responsibilities:

• Researching and developing state of the art pipelines for: analysing deployment domains, route feasibility checks, domain clustering and classification, representation learning and data coverage analysis.

• Researching and developing state of the art techniques and processes for assuring pre- and post-deployment data coverage across the company.

• Responsible for data interpretation, data governance, communicating findings from the validation, and creating dashboards for metrics management.

• Keeping up with the latest advances in computer vision and tracking research and applying relevant techniques to Oxa MetaDriver

• Contributing to the development tools and processes to support a common testing framework across the company, acquisition of data, ML frameworks and commercial operations

Benefits:

• Exciting role in a fast-growing startup

• Work across countries, follow EU expansion

• Ownership and career growth opportunities

• Competitive salary with benefits

• Young, hands-on teamAutonomy to define your success pathCelebratory parties, snacks, and drinksFlexible work: remote or officeSpacious offices (with a PlayStation)Pancake Wednesdays and monthly team activitiesFootball Table and Beer hourYearly Team Retreat for bonding

Education Requirements:

• you have a bachelor’s or master’s degree in computer science or related field

Other Requirements:

• fluent in python

• fluent in developing with databases (MySQL)

• knowledge of Git and Linux

• you speak fluent Dutch and/or English

• hands-on attitude and comfortable in a fast-moving start-up environment

• experience with data collection and processing is a plus

Responsibilities:

• Transport mode algorithm improvements

• Proactive recommendations

Experience Requirements:

• Significant experience deploying and securing production AI/ML infrastructure

• Deep understanding of popular security posture management tools and practices

• Strong familiarity with AI/ML concepts

• Previous experience in security services setup or at a large SaaS security company is highly desirable

Responsibilities:

• Work directly with customers to assess and enhance their AI/ML security posture

• Design and implement architectural patterns and proof of concepts

• Collaborate with cross-functional teams

Experience Requirements:

• Deep domain knowledge in LLM safety and/or evaluation techniques

• Extensive experience in designing, implementing, and maintaining production-ready ML code

• Comfortability with leading end-to-end projects and collaborating with researchers and engineers

• Adaptability and flexibility

Responsibilities:

• Work at the intersection of ML and Engineering

• Perform rigorous testing of the product features

• Push the envelope by implementing novel techniques

• Work closely with our policy, product, and engineering teams

Experience Requirements:

• Domain knowledge in LLM evaluation and data curation techniques

• Extensive experience in designing and implementing LLM benchmarking

• Adaptability and flexibility

Responsibilities:

• Own LLM evaluation processes and methods

• Generate high quality synthetic data, curate labels, and conduct rigorous benchmarking

• Deliver robust, scalable, and reproducible production code

• Push the envelope by developing methods for benchmarking

• Co-author papers, patents, and presentations

Experience Requirements:

• Deep domain knowledge in privacy-preserving ML

• Practical experience in techniques to attack or defend ML models

• Extensive experience in implementing multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Own an ML privacy vertical

• Collaborate with our engineering team to deliver real-world applications

• Generate high quality synthetic training data, train LLMs, and conduct rigorous evaluation and benchmarking

Experience Requirements:

• Deep domain knowledge in LLM safety techniques

• Extensive experience in designing, training, and implementing multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Own an LLM vertical with a focus on a specific safety domain

• Generate high quality synthetic data, train LLMs, and conduct rigorous benchmarking

• Deliver robust, scalable, and reproducible production code

• Push the envelope by developing novel techniques and research

• Co-author papers, patents, and presentations

Experience Requirements:

• Deep domain knowledge in Natural Language Processing

• Extensive experience in designing, implementing, and maintaining production-ready ML code

• Past experience in leading an end-to-end NLP feature

• Adaptability and flexibility

Responsibilities:

• Be responsible of a vertical for Dynamo AI’s state-of-the-art safety guardrails

• Perform rigorous testing of the product features

• Push the envelope by implementing novel techniques

• Work closely with our policy, product, and engineering teams

Experience Requirements:

• Deep research domain knowledge in LLM safety techniques

• Extensive research experience in aligning, training, and/or attacking multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Spearhead an LLM research domain with a focus on safety, quality, explainability, evaluation, and/or adversarial attacks

• Push the envelope by developing novel techniques and research

• Co-author papers, patents, and presentations

• Lead research projects end-to-end

• Deliver generalizable, scalable, and reproducible algorithms

Education Requirements:

• MS/PhD degree in Computer Science, Statistics, Applied Mathematics, Computational Biology, Computational Chemistry or other related subject

• Will also consider BS degrees in these areas for candidates highly qualified across other requirements or with significant work experience

Experience Requirements:

• 2+ years of experience on machine learning teams, ideally at a start-up

• 4+ years of ML research experience in industry or academia, with strong familiarity with PyTorch

Other Requirements:

• Track record of contributing to novel methods for state-of-the-art Deep Learning (in industry or through publications) including large-scale Transformers, Graph Neural Nets, ConvNets, etc.

• Experience with Python is required

• Relevant experience working in a Linux/UNIX environment with basic data engineering and scripting abilities

• Ability to understand business problems and how to build models that can quickly drive value, while prioritizing your research efforts accordingly

• Clearly communicate modeling setup and results at various levels of abstraction

Responsibilities:

• Scientifically direct the design and training of large-scale, state-of-the-art Deep Learning systems

• Develop novel architecture and training paradigms to lead the industry in unsolved scientific problems

• Collaborate with content experts from other domains (e.g., chemistry, physics, biology) to enable innovative feature-engineering and novel cross-disciplinary approaches

• Actively contribute to top-tier ML conferences and journals and attend core ML conferences to stay connected with the community and current trends

Education Requirements:

• PhD in Chemical Biology, Proteomics, or related field

Experience Requirements:

• 5+ years in industry experience focused on small molecule drug discovery at pharmaceutical or biotech companies, with a track record in leading small molecule proteomic initiatives

Other Requirements:

• Proven experience in proteomics research and small molecule drug discovery

• Track record in designing and executing complex scientific experiments

• Computational affinity, worked with computational biologists

• Experience in managing a team of PhD researchers

• Familiarity with AI applications in proteomics and drug discovery

• Strong budget management skills

• Excellent communication skills, adept at summarizing scientific progress for various audiences

Responsibilities:

• Drive the scientific strategy, aligning our proteomics research with AI-driven drug discovery initiatives

• Lead and nurture a team of PhD researchers, promoting a culture of innovation and discovery

• Oversee lab operations and facilities, maintaining an environment that fosters excellence and safety

• Plan and steer ambitious proteomics experiments, making key decisions to shape our scientific trajectory

• Prudently invest in state-of-the-art lab hardware to keep us on the cutting edge of proteomics research Bridge the gap between lab teams and computational workstreams, fostering a synergistic environment that maximizes data utility Manage and optimize the lab budget, ensuring resources are strategically allocated Provide regular updates on scientific progress, keeping stakeholders informed and inspired

Education Requirements:

• MSc or PhD degree in computational biology, bioinformatics or a related field

Experience Requirements:

• Possess mixed academic and/or industrial experience, preferably in the biotech industry

Other Requirements:

• Strong background in computational structural or systems biology

• Strong programming skills in Python, R and/or other languages

• Experience building reproducible and scalable computational biology workflows

• Experience designing and applying machine learning models

Responsibilities:

• Develop pilot capabilities and create large-scale data pipelines from the ground up

• Collaborate with other teams across VantAI and partnering organizations to achieve project goals by contributing code, analyses, benchmarks, optimizations and ideas to ongoing research-driven projects

• Integrate biological insights into the next generation of AI/ML models for drug discovery

• Validate and interpret computational predictions by working closely with experimentalists

Education Requirements:

• MSc/PhD degree in Chemistry, Computational Chemistry, Biochemistry, Chemical Engineering, or another related subject

Experience Requirements:

• Minimum 2 years (PhD) or 4 years (MSc) of post-graduate experience in small-molecule drug discovery

Other Requirements:

• Proven track-record in advancing drug discovery projects using in-silico methods; strong background in rational drug design

• Ability to adapt well to a fast-paced environment and get things done by combining creativity, problem-solving skills, and a can-do attitude to overcome obstacles

• Extensive experience in large-scale virtual screening using structure and ligand-based methods for hit identification and optimization

• Strong programming skills with at least 2 years of experience using Python for data analysis

• Excellent written and verbal communication skills along with a strong desire to work in cross-functional teams

Responsibilities:

• Lead small-molecule drug discovery projects using internal and external Machine Learning and CADD tools

• Drive drug discovery programs forward by quickly developing scalable tools to address specific project needs

• Work independently and in collaboration with Medicinal Chemists to prioritize small-molecule designs, clearly communicating the decisions to interdisciplinary audiences

• Collaborate with experts from other fields (e.g., Medicinal Chemistry, Machine Learning, Computational and Structural Biology, etc.) to advance integrated in-silico discovery platforms

• Design and execute large-scale virtual screening campaigns using both ligand and structure-based approaches

Benefits:

• Sport subscription

• Medical insurance

• Training budget

• Modern Office, no dress code & young team

• Bonus policy

Experience Requirements:

• Experience with deep learning algorithms applied to various areas of Computer Vision

• Familiarity with popular architectures such as Vision Transformers, DeepLabv3, SegFormer, etc

• Good understanding of transfer learning and popular augmentation techniques

• Proven experience in tackling common computer vision tasks including image classification, detection, segmentation, face recognition, pose estimation, etc

• Working knowledge of CV-related training procedures, validation techniques and datasets

Other Requirements:

• The ability to apply machine learning to real-life problems

• Good knowledge of machine learning algorithms, model training, hyper parameter tuning

• Working knowledge of deep learning models, loss functions, and performance measures

• Strong Python skills, hands-on proficiency in using machine learning tools: Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras

• The ability to share your knowledge and willingness to learn continuously

• English B2+ level at minimum

Responsibilities:

• Developing Deep Learning solutions in various Computer Vision tasks

• Developing the methodology and assessment criteria to measure solution performance

• Tracking and implementing recent advancements in Deep Learning and Computer Vision areas

• Maintaining internal ML-products

Benefits:

• Sport subscription

• Medical insurance

• Training budget

• Modern Office, no dress code & young team

• Bonus policy

Experience Requirements:

• Experience with deep learning algorithms applied to various areas of Computer Vision

• Familiarity with popular architectures such as Vision Transformers, DeepLabv3, SegFormer, etc

• Good understanding of transfer learning and popular augmentation techniques

• Proven experience in tackling common computer vision tasks including image classification, detection, segmentation, face recognition, pose estimation, etc

• Working knowledge of CV-related training procedures, validation techniques and datasets

Other Requirements:

• The ability to apply machine learning to real-life problems

• Good knowledge of machine learning algorithms, model training, hyper parameter tuning

• Working knowledge of deep learning models, loss functions, and performance measures

• Strong Python skills, hands-on proficiency in using machine learning tools: Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras

• The ability to share your knowledge and willingness to learn continuously

• English B2+ level at minimum

Responsibilities:

• Developing Deep Learning solutions in various Computer Vision tasks

• Developing the methodology and assessment criteria to measure solution performance

• Tracking and implementing recent advancements in Deep Learning and Computer Vision areas

• Maintaining internal ML-products

Benefits:

• Best in Class Medical Insurance

• Mental Health Programs

• Contemporary Leave Policy

• Company Sponsored Offsites

Education Requirements:

• Bachelor’s or Master's degree in Linguistics, Computational Linguistics, Gujrati Language, or a related field

Experience Requirements:

• 0.6-4 Experience

Other Requirements:

• Proficiency in Gujrati, including an in-depth understanding of grammar, syntax, and cultural nuances

• Understanding with NLP (Natural Language Processing) and conversational AI technologies

• Strong communication skills and the ability to work collaboratively in a team environment

• Attention to detail and a passion for language and linguistic analysis

• Previous experience in linguistic analysis, translation, or NLP projects is desirable

• Ability to adapt to a dynamic work environment and handle multiple tasks simultaneously

• Experience in working with language data, annotation tools, and linguistic databases

• Understanding of machine learning concepts and their application to language processing

Responsibilities:

• Conduct linguistic analysis of the Gujrati language to identify linguistic patterns, nuances, and cultural elements relevant to the conversational AI domain

• Collaborate with the development team to create and refine language models for conversational AI in Gujrati, considering syntax, grammar, and vocabulary

• Translate and localize content from English or other languages into Gujrati, ensuring cultural appropriateness and linguistic accuracy

• Conduct rigorous testing and quality assurance of the conversational AI system to verify the linguistic accuracy and naturalness of the output in Gujrati

• Work on data collection, annotation, and validation tasks for training conversational AI models in Gujrati, ensuring high-quality, diverse, and representative language data