Applied AI Researcher

October 25

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Articul8 AI

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Description

• Articul8 AI is seeking an exceptional Applied AI Researcher to join us in shaping the future of Generative Artificial Intelligence (GenAI). • Responsible for designing, developing, and scaling novel algorithms and models able to handle diverse modalities. • Collaborate with cross-functional teams and external partners to drive innovations in enterprise-grade GenAI.

Requirements

• Education: PhD degree in Computer Science, Machine Learning, or a related field; or alternatively, BSc/MSc Degree and experience (3+ years post BSc graduation) as a practicing researcher. • Professional experience: proven track record as a researcher 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: • 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. • Proven track record of publications in top-tier conferences and journals

Benefits

• 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