Research Intern, Inference (Fall 2026)
As an AI Infrastructure Engineer at Together, the responsibilities include participating in on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to support scaling to a large number of concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture in terms of reliability, performance, and availability, and planning the growth of Together AI's infrastructure.
Member of Technical Staff (Machine Learning Engineer)
Translate cutting-edge research into production-ready machine learning systems. Design, build, and deploy end-to-end ML models and pipelines. Develop and optimize models for image and video processing. Own the full ML lifecycle including experimentation, training/fine-tuning, evaluation, and deployment. Rapidly prototype using open-source models and adapt them for product needs. Conduct experiments, analyze results, and iterate to improve performance. Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale. Participate with advancements in machine learning and apply them to continuously improve products.
Warehouse Supervisor (Temporary)
Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.
Software Engineer, AI Product (Canada)
As a Senior Applied AI Engineer at Vanta, you will work cross-functionally to design and implement AI-powered features that deliver customer value and integrate large language models (LLMs) with Vanta's existing products and systems. You will collaborate with product engineers across Vanta to understand how AI systems can accelerate product adoption, instrument evaluations, guardrails, and monitoring, and review customer usage to continually improve quality. Additionally, you will collaborate with AI Platform engineers on foundational AI systems and tooling to accelerate product teams, make pragmatic tradeoffs considering business priorities, user experience, and sustainable technical foundation, mentor engineers, champion good technical and product instincts, and model a collaborative, high-ownership engineering culture.
Engineering Manager, AI
As an Engineering Manager at Vanta, you will build and scale a high-performing team by hiring strategically to fill skill gaps as the team grows. You will coach, mentor, and create an environment that enables your team to do their best work and deliver for the business. You will set direction and guide technical strategy for AI agent and downmarket products, ensuring long-term value aligned with Vanta's business priorities. You will partner closely with product, design, and AI platform teams to ship customer-facing AI features that automate audit work while maintaining human-in-the-loop controls. Additionally, you will champion best practices for applied AI, including prompt engineering, retrieval-augmented generation (RAG), agentic frameworks, and quality evaluation. You will also navigate rapid change and ambiguity with adaptability, iterating quickly on roadmaps as the team's charter and direction evolve.
Software Engineer, ML Data Infrastructure
The Software Engineer, ML Data Infrastructure will collaborate with engineers to build advanced AI design experiences, tackle complex technical challenges including scaling distributed systems and enabling generative media experiences, build robust data infrastructure at petabyte scale ensuring reliability and performance across multi-modal training pipelines, optimize data processing workflows for high throughput involving distributed systems, TPU infrastructure, and large-scale storage, and partner with research scientists to understand data requirements and translate them into production-grade systems to accelerate model development cycles.
Research Engineer / Research Scientist (Pre-training)
In this role, you will push the frontier of visual generative models. You will work on large-scale pre-training for text-to-image foundation models, shaping objectives, algorithms, data, and systems, and turn novel ideas into models that power products used by millions of users. You will work with a creative and ambitious team of researchers and engineers building the future of the creative economy.
Full Stack Product Engineer
As a Full-Stack Product Engineer at Ideogram, you will build products that bring generative AI directly to creators, working across the entire technology stack from designing user experiences to optimizing backend systems that serve millions. Your focus will be on shipping features that users love by combining product intuition, strong ownership, and user empathy. You will design APIs and data models to support evolving product needs, utilize AI-native engineering tools to speed up development, debugging, and understanding of the codebase, and work effectively across frontend and backend systems. You will also be responsible for explaining technical concepts to both technical and non-technical stakeholders, participating in constructive code reviews, collaborating with the team, and taking full responsibility for the outcomes of your work, not just the code.
Optical Engineer - Freelance AI Trainer
Contributors may design original optics problems that simulate real physics research workflows, ensure these problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics, base problems on real research challenges or practical applications from optics and physics practice, and document problem statements clearly with verified correct answers.
Junior Software Engineer
Oversee the end-to-end lifecycle of data acquisition and management for foundation models across 3D, video, image, and audio. Identify and acquire diverse datasets from public and commercial partners while managing complex technical and legal requirements. Collaborate with research teams to ensure data sources align with specific model training and fine-tuning needs. Manage technical lifecycle of large-scale data, including ingestion, curation, and AWS S3 storage optimization, ensuring system reliability and code quality. Develop internal tools and standards to make datasets searchable, accessible, and efficiently indexed for research. Partner with legal team to mitigate risks, ensure global regulatory compliance, and manage sensitive data protection rules. Represent the company in legal matters including providing testimony regarding data usage and licensing. Lead data vendor management by negotiating Master Services Agreements and Statements of Work, oversee partnerships for data annotation, evaluation, and collection projects. Drive cross-functional alignment between technical leads and researchers to ensure data strategy supports the company product roadmap.
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