2 Kaggle Jobs

AI Developer Req number: R5051 Employment type: Full time Worksite flexibility: Hybrid Who we are CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise. Job Summary We’re seeking a problem-solving AI Developer with 3–5 years of hands-on experience in building and deploying deep learning models, including RAG systems and LLM fine-tuning. You’ll work on cutting-edge projects, contribute to open-source initiatives, and solve complex AI challenges. This is a Full-time and Hybrid position. Job Description What You’ll Do Design and implement scalable deep learning models, including RAG architectures and LLM-based solutions. Fine-tune and optimize LLMs for specific use cases (e.g., text generation, summarization). Collaborate on open-source projects and research initiatives. Optimize model performance for latency, accuracy, and scalability. What You'll Need 3–5 years of professional experience in AI/ML development. Expertise in Python and frameworks like TensorFlow/PyTorch. Proven experience with neural networks (CNNs, RNNs, Transformers) and building RAG systems. Hands-on experience in fine-tuning LLMs (e.g., GPT, Llama, Mistral) for domain-specific tasks. Strong portfolio of open-source contributions (GitHub, Kaggle, etc.). Ability to debug, optimize, and deploy models in production environments. Critical thinker with a track record of research-driven problem-solving. Preferred Experience with diffusion models or reinforcement learning. Publications in top AI conferences (NeurIPS, ICML, CVPR). Familiarity with MLOps tools (MLflow, Kubeflow) and vector databases (Pinecone, FAISS). Knowledge of cloud platforms (AWS/GCP/Azure). Physical Demands This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc. Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor. Reasonable accommodation statement If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

The Team : As a member of the Data Transformation - Cognitive Engineering team you will work on building and deploying ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead deployment of AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Lead a highly skilled and technically strong team (including leadership) Contribute to solving high complexity, high impact problems Build production ready pipelines from ideation to deployment Responsibilities: Design, Develop and Deploy ML powered products and pipelines Mentor a team of Senior and Junior data scientists ML Engineers in delivering large scale projects Play a central role in all stages of the AI product development life cycle, including: Designing Machine Learning systems and model scaling strategies Research & Implement ML and Deep learning algorithms for production Run necessary ML tests and benchmarks for model validation Fine-tune, retrain and scale existing model deployments Extend existing ML librarys and write packages for reproducing components Partner with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Interpret results and present them to business leaders Manage production pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Lead and mentor by example, including project scrums Technical Requirements: Proven track record as a senior lead ML engineer Expert proficiency in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Excellent exposure to large scale model deployment strategies and tools Excellent knowledge of ML & Deep Learning domain Solid exposure to Information Retrieval, Web scraping and Data Extraction at scale Exposure to the following technologies - R-Shiny/Dash/Streamlit, SQL, Docker, Airflow, Redis, Celery, Flask/Django/FastAPI, PySpark, Scrapy Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Open to learning new technologies and programming languages as required A Masters PhD from a recognized institute in a relevant specialization Good to have: 6-7+ years of relevant experience in ML Engineering Prior substantial experience from the Economics/Financial industry Prior work to show on Github, Kaggle, StackOverflow etc.