Role Description We are looking for a highly analytical and computationally strong professional with a solid research background in mathematics or quantitative fields. In this role, you will design advanced benchmark tasks for multi-agent AI systems, focusing on complex mathematical reasoning, algorithmic problem-solving, and verifiable computational outputs. You will contribute by crafting challenging problems, building validation systems, and structuring tasks that require decomposition into coordinated sub-solutions. - Commitments Required: 8 hours per day with an overlap of 4 hours with PST. - Employment type: Contractor assignment (no medical/paid leave) - Duration of contract: 4 weeks+ - Location: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria, Turkey, Vietnam - Interview: take home assessment (60min) + short interview Responsibilities - Design and build multi-agent benchmark tasks requiring multi-step mathematical reasoning and algorithmic problem-solving. - Create complex, decomposable problems across domains such as: - Competition mathematics - Numerical analysis - Combinatorial optimization - Statistical inference - Develop verification scripts to validate: - Numerical outputs (with tolerance thresholds) - Proof correctness and logical steps - Algorithmic outputs and constraints - Write clear, structured problem statements with precise notation and defined outputs. - Design task decomposition strategies for parallel or multi-agent execution. - Implement computational solutions and validation pipelines using Python. - Work with containerized environments (Docker) for reproducibility and evaluation. Qualifications - 5+ years in mathematics, quantitative research, or computational science — competition math, university-level mathematics, or quantitative research background. - Python programming — NumPy, SciPy, or symbolic computation (SymPy). - Experience writing mathematical proofs or formal derivations. - Ability to create problems with precise, verifiable answers — not subjective or open-ended. - Experience with AI coding benchmarks (SWE-bench, Terminal-bench). - Comfortable with Docker — writing Dockerfiles, building images, and debugging container issues. - Understanding of numerical methods — floating point tolerance, convergence criteria, error bounds. Nice to Have - Experience creating competition math problems (AMC, AIME, Putnam, IMO). - Background in theoretical computer science or advanced mathematics research. - Exposure to automated theorem proving or formal verification. - Familiarity with AI reasoning benchmarks (GSM8K, MATH, AIME, GPQA, ARC-AGI). - Experience in large-scale numerical or scientific computing.

Role Description We are seeking an experienced software engineer with experience in AI and machine learning solutions. As an engineer, you will be responsible for implementing AI-driven solutions for a wide range of applications. Your focus will include developing intelligent systems and chatbots using predictive models, LLMs, RAG and other technologies that provide substantial business value. You will also play a pivotal role in working with a talented team of engineers to deliver impactful and innovative solutions. This is a hands-on role that requires both technical expertise and a strong strategic mindset. Qualifications - At least 5 years of experience in software development with relevant experience in AI/ML design and development. - Background in delivering scalable AI solutions. - Bachelor’s degree in Computer Science or equivalent. - Professional certifications in AI or related areas are a plus. Requirements - Proficient in Python with knowledge of RDBMS, ORM and frameworks like Django, Flask or FastAPI. - Working knowledge of ReactJS or any other JS framework/library. - Proven experience in designing and deploying chatbots/conversational agents using NLP techniques and frameworks such as Rasa, DialogFlow, or similar platforms. - Knowledge of Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), including GPT models, and similar architectures. - Hands-on experience with predictive modeling techniques including time series forecasting, regression, classification, and anomaly detection is a plus. - Knowledge of advanced AI techniques like reinforcement learning, deep learning, and computer vision is a plus. - Experience with cloud computing platforms (e.g. AWS, Google Cloud, Azure). - Familiarity with DevOps practices and CI/CD pipelines for deployment. - Strong analytical and problem-solving skills with a drive for optimization and results. - Excellent verbal and written communication skills with the ability to document processes and collaborate effectively with diverse teams. Benefits

About the Team The AI Center of Excellence leverages advanced machine learning, LLMs, and agentic systems to enhance threat detection and automate security workflows for our global customers. We transform 20+ years of threat intelligence into proactive defense features through a collaborative, research-driven engineering environment. About the Role - As a Data Scientist (SE-2), your primary responsibility will be to contribute to the end-to-end development, evaluation, and monitoring of ML and LLM-based security features. - Execute data acquisition, cleaning, and feature engineering to prepare high-quality datasets for security modeling. - Build and evaluate supervised and unsupervised ML models, including classification, clustering, and anomaly detection. - Develop and optimize LLM-based workflows, including prompt engineering and the implementation of RAG pipelines. - Support the deployment and observability of models on AWS infrastructure using established CI/CD pipelines. The skills and qualities you'll bring include: - A courageous and curious mindset, demonstrating a strong ability to learn new technologies and operate in ambiguous problem spaces. - Exceptional collaboration skills with the ability to work cross-functionally with senior scientists and engineers to ship production features. - Strong ownership and principled decision-making when evaluating model performance and data quality. - 2-5 years of professional experience in Data Science or ML Engineering roles. - Proficiency in Python and its scientific ecosystem, specifically Pandas, NumPy, and scikit-learn. - Hands-on experience building and tuning supervised and unsupervised machine learning models. - Working knowledge of AWS ML services, including SageMaker, S3, Bedrock, and Lambda. - Foundational exposure to LLM orchestration frameworks such as LangChain or HuggingFace Transformers. - Understanding of deep learning frameworks (PyTorch or TensorFlow) for NLP or sequence-based problems. - Familiarity with model evaluation metrics and explainability techniques like SHAP or LIME. - Basic understanding of CI/CD pipelines (GitHub Actions/Jenkins) and version control for ML workloads. - Experience monitoring model performance and drift using tools like CloudWatch. We know that the best ideas and solutions come from multi-dimensional teams. That's because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don't be shy - apply today. #LI-AK1 About Rapid7 At Rapid7, our vision is to create a secure digital world for our customers, our industry, and our communities. We do this by harnessing our collective expertise and passion to challenge what's possible and drive extraordinary impact. We're building a dynamic and collaborative workplace where new ideas are welcome. Protecting 11,000+ customers against bad actors and threats means we're continuing to push the envelope just like we' ve been doing for the past 20 years. If you 're ready to solve some of the toughest challenges in cybersecurity, we're ready to help you take command of your career. Join us.

Role Description We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as Senior Solutions Consultant, Resident Solutions Architect, or Senior Resident Solutions Architect. You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership. As a Data & AI Platform Architect (Professional Services) (Internal Title - Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead. The impact you will have: - Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases. - Work with engagement managers to scope a variety of professional services work with input from the customer. - Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications. - Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Provide an escalated level of support for customer operational issues. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. Qualifications - Extensive experience in data engineering, data platforms & analytics. - Comfortable writing code in either Python or Scala. - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one. - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals. - Familiarity with CI/CD for production deployments. - Working knowledge of MLOps. - Design and deployment of performant end-to-end data architectures. - Experience with technical project delivery - managing scope and timelines. - Documentation and white-boarding skills. - Experience working with clients and managing conflicts. - Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 10% of the time. - [Preferred] Databricks Certification but not essential. Benefits - At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. - For specific details on the benefits offered in your region click here .