About Stepful: Stepful is reimagining allied healthcare training by offering affordable, online, instructor-led, and AI-supported programs that help learners—regardless of background or circumstance—launch high-demand healthcare careers. In addition to our direct-to-consumer training, Stepful partners with leading healthcare institutions to address the growing national shortage of healthcare workers. Our graduates, including Medical Assistants, Pharmacy Technicians, Nurses, and more, form the talent pipelines at major employers like CVS, NY-Presbyterian, HCA, Providence, and Walgreens. Stepful is backed by Y Combinator, Reach Capital, and AlleyCorp, with a recent $31.5M Series B led by Oak HC/FT. We were named the #1 EdTech company in the U.S. by TIME for 2025. We’re improving access to quality healthcare for everyone, everywhere, and improving access to healthcare careers for those who need them most Our values: We credit much of our success to our exceptional team. We’re looking for mission-driven builders who thrive in fast-paced, ambiguous environments, and embody our four core values: - Care first: We do whatever it takes for our students to succeed. - Learn quickly: We test, learn with data, and iterate. - Build together: We win when we rely on each other. - Own it: We show up, take initiative, and show pride. The opportunity: We are seeking an experienced Adjunct Instructor to join Stepful on a contract basis to teach virtual didactic courses within our Board of Nursing–approved Practical Nursing program. In this role, you will support student success by delivering engaging online instruction that helps prepare future nurses for clinical practice and licensure. This opportunity is well suited for a Registered Nurse with faculty experience in RN or LPN education who enjoys teaching in a virtual classroom environment. Didactic courses take place Monday–Thursday from 6:30–9:00pm EST. This is a 1099 contract role, with hours varying based on the number of courses taught. What you’ll do: - Teach live, virtual didactic lessons via Stepful’s LMS - Deliver curriculum content, answer student questions, and provide timely feedback - Act as a subject matter expert in practical nursing education - Foster a positive and supportive learning environment for students What you’ll bring: - 2+ years of experience as faculty in an RN or LPN education program - 2+ years of professional experience as a Registered Nurse, with 5+ years of varied nursing experience across clinical practice, nursing education, and/or administration - Bachelor’s degree in Nursing (BSN) - Active, unencumbered Michigan RN license - Ability to collaborate effectively with faculty, staff, students, and external partners Interview Process: - Intro Call with Talent Team - Case Study Assignment - Final Interview The hourly pay rate for this opportunity is $50.00/hour. Individual pay may vary from the target range and is determined by a number of factors including experience, internal pay equity and other relevant business considerations. Stepful is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic.

Role Description A ABZ Group está em busca de profissionais da área de Marinharia/Cabotagem para atuar em um grande projeto de um de nossos parceiros. Se você busca novos desafios e quer fazer parte de um time global e especializado, inscreva-se e venha construir sua carreira com o #ABZteam! Função: Oficial de Máquinas Qualifications - CIR - III/1, III/2 ou III/3 - Inglês avançado (será testado) - Disponibilidade início imediato em escala 28x28 - Experiência prévia na função - Certificações marítimas de acordo com a categoria - Experiência em FLOTEL será considerado um diferencial Requirements - Embarcação - Flotel

• Design, develop, and maintain high-performance, scalable, and secure backend services, primarily using Python and frameworks like FastAPI • Translate ambiguous business and technical requirements into concrete software designs and actionable tasks for cross-functional teams • Work with OLTP databases, including schema design, migration strategies, and performance optimization • Integrate SmartAsset services with internal and external APIs, including third-party platforms and existing AWS infrastructure • Ensure secure ingress and egress of data within our private network environments • Contribute to the design and implementation of our CI/CD pipelines to ensure continual improvements to our cycle time • Manage and optimize AWS services, including IAM roles and policies • Gain a deep understanding of how our Python applications integrate with our Kubernetes (EKS) and future ECS-based infrastructure • Operate and maintain production applications at scale, ensuring high availability, performance, and reliability • Design and implement data collection pipelines specifically for Large Language Models (LLMs) • Contributed to shared data architecture and data governance practices to ensure the persistence of structured data suitable for analytics and model training • Explore, integrate, and tune various LLM-related technologies, such as Retrieval Augmented Generation (RAG) systems, and addressing potential scaling challenges • Investigate and implement agentic technologies, such as tool calling frameworks (e.g., AutoGen), to enhance LLM capabilities • Rapidly prototype user interfaces for internal tools and data exploration, leveraging frameworks like Streamlit, Gradio, or other similar tools that facilitate quick iteration and integration without persistent websockets

• Design, develop, and deploy machine learning models to solve business problems across large-scale datasets. • Build and optimize machine learning pipelines for data preparation, model training, and inference. • Collaborate with data engineers and software engineers to develop scalable ML infrastructure and pipelines. • Research and implement modern machine learning techniques, including deep learning and large language models where appropriate. • Work closely with product and cross-functional teams to translate business requirements into technical solutions. • Deploy and maintain machine learning models in production environments. • Monitor model performance, conduct experiments and A/B testing, and continuously improve model accuracy and reliability. • Contribute to the team's engineering best practices, including code reviews, documentation, and knowledge sharing.