Applied Mathematician (AI/ML) - Global

About us: 

At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business. We believe in using our advantages to make a positive impact on the world and inspiring others to do the same. 

Job Description: 

Articul8 AI is seeking an exceptional mathematician to join us in shaping the future of Generative Artificial Intelligence (GenAI). We are looking for a mathematician with a proven track record of translating cutting-edge research into practical product solutions.  

As a member of our AI Mathematics team, you will be responsible for designing, developing, and scaling novel algorithms and models capable of handling diverse modalities such as text, images, audio, video, and time series data. You will also develop new model architectures, carry out benchmark studies, and optimize the performance metrics of current technologies.   

This position offers exciting opportunities to work closely with cross-functional teams and external partners to drive innovations in enterprise-grade GenAI. 

Responsibilities: 

• Serve as the subject matter expert and lead developer for key GenAI technologies, encompassing various domains such as data pipelines, training and fine-tuning, reinforcement learning, model architecture development and optimization, multi-expert systems, and multimodal models and techniques. 

• Play a pivotal role in conceiving, implementing, and scaling pioneering technologies through all stages, from initial brainstorming and experimentation to validation and deployment. 

• Collaborate with cross-functional teams, including Product Technology, Engineering, Quality Assurance, and Customer Success, to seamlessly incorporate innovation and maintain our product technology leadership. 

• Participate in high-level technical discussions, contributing to technology assessment and roadmap planning. 

• Continuously stay abreast of emerging trends and advancements in GenAI and associated fields, while disseminating appropriate research results at top-tier conferences and journals. 

• Mentor and guide junior team members and help build a strong culture of rapid innovation.  

Required Qualifications: 

• Education: PhD degree in Mathematics, Computer Science, Machine Learning (ML), or a related field; or alternatively, MSc Degree and experience (3+ years post MSc graduation) as a practicing mathematician. 

• Professional experience: proven track record as a mathematician working in the design and implementation of ML/AI models and algorithms aimed at solving complex, real-world problems. A strong background in parallel/distributed computing (preferably on the cloud). 

• Core technical skills: 

  • Advanced Geometry Understanding: Solid grasp of differential, algebraic, and computational geometry to analyze spatial structures in data. 

  • Time Series Analysis: Expertise in statistical modeling and forecasting techniques for analyzing temporal data trends and patterns. Proficiency in applying wavelet transforms for multi-resolution signal processing and feature extraction. 

  • PyTorch Geometric Proficiency: Practical experience with the PyTorch Geometric library for implementing graph-based deep learning models. 

  • Graph Neural Networks (GNNs) Implementation: Skills in designing, training, and optimizing GNNs to handle complex, non-Euclidean data structures. 

  • Knowledge Graph Extraction Insights: Ability to extract, analyze, and leverage semantic relationships from knowledge graphs to improve model interpretability and performance. 

  • Machine Learning: A solid understanding of machine learning algorithms, neural networks, and deep learning techniques. Familiarity with popular frameworks such as PyTorch and/or TensorFlow. 

  • Probability Theory and Statistics: Knowledge of probability theory and statistical concepts. This includes topics like random variables, distributions, Bayesian methods, hypothesis testing, and confidence intervals. 

  • Mathematics: Strong foundations in algebra, calculus, optimization, graph theory, and numerical methods. 

  • Natural Language Processing (NLP): expertise with techniques used in text preprocessing, tokenization, part-of-speech tagging, parsing, sentiment analysis, topic modeling, and word embeddings. 

  • Computer Vision: strong foundations in techniques used in tasks such as include object detection, segmentation, optical flow estimation, feature extraction, tracking, and image processing. 

  • Data Wrangling and Preparation: expertise in handling large datasets, data cleaning, normalizing, transforming, and preparing them for model training. 

  • Model Evaluation and Interpretation: ability to assess model performance, compare different models, interpret results, and identify potential issues. Understanding evaluation metrics, bias-variance tradeoff, overfitting, underfitting, regularization techniques, and hyperparameter tuning. 

• Programming Skills:  

  • Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial. Ability to write clean, efficient, and modular code for data processing and algorithm implementation. 

  • Graph Query Language Proficiency: Familiarity with graph databases and query languages such as Cypher (Neo4j), Arango QL or SPARQL. Experience in querying and manipulating complex graph data structures. 

  • Optimization Libraries: Ability to formulate and solve optimization problems relevant to data science and machine learning. Hands-on experience with optimization tools like SciPy’s optimize module, CVXPY, or other industry-standard libraries. 

  • Clustering Techniques: Skills to apply clustering techniques for uncovering patterns and insights in large datasets. Knowledge of both classical (K-means, hierarchical clustering) and advanced clustering methods (DBSCAN, spectral & topological clustering) 

• Proven track record of publications in top-tier conferences and journals 

Preferred Qualifications: 

• Master’s or PhD in mathematics, computer science, or related technical fields. 

• 3+ years of a hands-on experience as mathematician in the applied ML/AI space 

• Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments. 

• Experience with cloud computing platforms such as AWS, Azure, or GCP. 

Professional Attributes: 

• Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence. 

• Collaboration and Communication: proficiency in working within cross-functional teams - communicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives. 

• Project Management and Prioritization: demonstrated aptitude in balancing multiple projects, deadlines, and allocating time efficiently between short-term objectives and long-term goals. Ability to follow and oversee projects, coordinating resources, setting milestones, monitoring progress, and adjusting plans accordingly. 

• Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results. 

• Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base. 

• Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others' contributions.  

By joining our team, you become part of a community that embraces diversity, inclusiveness, and lifelong learning. We nurture curiosity and creativity, encouraging exploration beyond conventional wisdom. Through mentorship, knowledge exchange, and constructive feedback, we cultivate an environment that supports both personal and professional development. 

Your future experience at Articul8 will include continuous learning and growth opportunities as we embark on an exciting journey to disrupt the status quo. If you're excited about joining a team that's passionate about making a difference, we want to hear from you. 

In addition to our competitive salary and benefits package, we offer a range of perks and programs designed to help you succeed, including: 

• Professional development opportunities, including training and mentorship programs 

• Flexible work arrangements, including remote work options 

• Access to the latest technologies and tools 

• Regular social events and team-building activities 

• A supportive and inclusive work environment 

 If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team. Join us on this adventure and help shape the future of Generative AI in the enterprise.