Scale AI

About the Company

At Scale, our mission is to accelerate the development of AI applications. We believe that to make the best models, you need the best data.

The Scale Generative AI Platform leverages your enterprise data to customize powerful base generative models to safely unlock the value of AI. The Scale Data Engine consists of all the tools and features you need to collect, curate and annotate high-quality data, in addition to robust tools to evaluate and optimize your models. Scale powers the most advanced LLMs and generative models in the world through world-class RLHF, data generation, model evaluation, safety, and alignment.

Scale is trusted by leading technology companies like Microsoft and Meta, enterprises like Fox and Accenture, Generative AI companies like Open AI and Cohere, U.S. Government Agencies like the U.S. Army and the U.S. Airforce, and Startups like Brex and OpenSea.

Listed Jobs

Company Name

Scale AI

Job Title

Applied AI Engineer, Enterprise

Job Description

**Job Title** Applied AI Engineer, Enterprise **Role Summary** A forward‑deployed ML engineer who collaborates directly with enterprise customers to design, train, and deploy production‑grade generative AI services. The position blends customer engagement, data‑driven experimentation, and production‑ready ML engineering. **Expectations** - 3+ years of engineering experience in a client‑facing capacity. - Minimum 2 years of model training experience, translating business requirements into data/model solutions. - Proficient in Python, with experience writing, testing, and debugging code in production systems. - Strong analytical mindset; able to conduct data‑driven experiments focused on metric improvement. - Comfortable working in cloud environments (AWS, GCP) and deploying ML workloads. - Excellent communication skills for explaining technical concepts to non‑technical stakeholders. - Flexible learner, capable of managing multiple priorities in ambiguous settings. **Key Responsibilities** - Own and optimize enterprise clients’ generative AI challenges; serve as the ML voice in technical discussions. - Conduct data‑centric experiments to iteratively improve LLM/RAG models and performance metrics. - Translate business requirements into technical specifications and ML solutions. - Design, develop, and production‑grade deploy Python code across both client and vendor codebases. - Collaborate cross‑functionally with data, product, and infrastructure teams to ensure integration of AI services. - Engage with client teams onsite and virtually, building deep stakeholder relationships. - Provide clear, concise explanations of model behavior, limitations, and best practices to diverse audiences. **Required Skills** - Python programming (numpy, pandas, common ML libraries). - Machine learning model training, evaluation, and tuning. - Cloud deployment (AWS or GCP) and experience building ML workflows in the cloud. - Data‑driven experimentation and analytics. - Strong debugging and testing capabilities. - Effective verbal and written communication with technical and non‑technical stakeholders. - Ability to gather requirements and translate them into actionable technical plans. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent engineering experience). - No mandatory certifications required. ---

London, United kingdom

On site

Junior

29-10-2025

Company Name

Scale AI

Job Title

Machine Learning Research Scientist/ Engineer, Agents

Job Description

**Job Title** Machine Learning Research Scientist / Engineer, Agents **Role Summary** Lead research and development of autonomous agent technologies. Drive data strategy and prototype LLM‑based agents that interact with environments such as browsers, code repositories, and GUIs. Translate research findings into scalable products and benchmark agent performance across real‑world tasks. **Expectations** - Minimum 3 years of advanced ML research or product development experience. - Proven track record of publications in top conferences (ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.). - Ability to rapidly prototype, debug, and iterate research models. - Strong written and oral communication; cross‑functional collaboration. **Key Responsibilities** 1. Design and conduct cutting‑edge experiments on LLM agents, planning algorithms, and reward signals. 2. Define and curate the data landscape required for browser, code, and GUI agents. 3. Prototype new agent architectures and evaluation pipelines using PyTorch, JAX, or TensorFlow. 4. Benchmark agent performance across diverse external environments and publish results. 5. Develop and maintain robust data programs to enhance LLM agentic capabilities. 6. Translate research insights into production‑ready solutions in collaboration with engineering teams. 7. Engage with customer researchers to shape research direction and product strategy. **Required Skills** - Advanced proficiency in PyTorch, JAX, or TensorFlow for building LLMs and agent models. - Deep understanding of large‑language model fundamentals, planning algorithms, and reward design. - Experience prototyping ML models, debugging, and iterating on research prototypes. - Practical exposure to cloud ML pipelines (AWS or GCP). - Strong analytical and problem‑solving skills; ability to synthesize research literature into actionable strategies. - Excellent communication and teamwork across research, product, and engineering functions. **Required Education & Certifications** - PhD or Master’s degree in Computer Science, Machine Learning, or a closely related field. - Demonstrated publication record in peer‑reviewed conferences (top ML venues). ---

New york city, United states

Hybrid

Junior

29-10-2025

Company Name

Scale AI

Job Title

Software Engineer - New Grad

Job Description

**Job title** Software Engineer – New Graduate **Role Summary** Entry‑level software engineer building and scaling AI‑enabled products and services that power Scale’s labeling platform and data infrastructure. Responsibilities include developing full‑stack web applications, integrating APIs, designing data pipelines, and implementing machine‑learning components to improve labeling quality, fraud detection, and user experience. **Expectations** - Graduate in Fall 2025 or Spring 2026 with a bachelor’s degree (or equivalent) in Computer Science, Electrical & Computer Engineering, Computer Engineering, Statistics, or a related field. - Previous product or software engineering internship with a proven record of delivering high‑quality features at scale. - Comfortable shipping end‑to‑end products, iterating based on customer and data insights, and maintaining code quality through testing and continuous integration. **Key Responsibilities** - Design, develop, and maintain full‑stack web applications that support large‑scale labeling workflows and AI model management. - Build and optimize data processing systems capable of handling high‑volume streams and batch jobs. - Implement fraud‑detection and churn‑prediction modules using ML models integrated with operational systems. - Create and refine UI/UX tools that enable 100 k+ labelers to complete billions of tasks efficiently. - Collaborate with product managers, data engineers, and customers to define requirements, prioritize features, and iterate on solutions. - Write automated tests, perform code reviews, and ensure robust CI/CD pipelines. - Troubleshoot, debug, and improve performance across backend services, databases, and frontend components. **Required Skills** - Full‑stack development: TypeScript, React, Python. - Database proficiency: MongoDB (or similar NoSQL). - Experience with RESTful API design, authentication, and third‑party integrations. - Ability to design and implement scalable data pipelines and batch jobs. - Strong understanding of software engineering best practices: version control (Git), unit/integration testing, CI/CD, and code quality tooling. - Problem‑solving mindset, effective communication, and teamwork. **Required Education & Certifications** - Bachelor’s degree (or equivalent) in Computer Science, Electrical & Computer Engineering, Computer Engineering, Statistics, or a related discipline, completed by Fall 2025 or Spring 2026. - No mandatory certifications specified.

San francisco bay, United states

Hybrid

11-11-2025

Company Name

Scale AI

Job Title

Machine Learning Research Intern (Summer 2026)

Job Description

**Job Title:** Machine Learning Research Intern (Summer 2026) **Role Summary:** Conduct research to develop next-generation AI systems with a focus on safety, reliability, and alignment, integrating technical applications and cutting-edge research in areas like generative AI, synthetic data, and model evaluation. Collaborate on hybrid human-machine systems for enterprise AI applications. **Expectations:** - Currently enrolled in a BS/MS/PhD program in Machine Learning, Deep Learning, Natural Language Processing (NLP), or Computer Vision. - Graduation date: Fall 2026 or Spring 2027. - Demonstrated research experience or publications in Large Language Models (LLMs), NLP, multimodal systems, safety, evaluation, or related fields. - Proficiency in Python, JavaScript, or similar programming languages. - Fluency in written and spoken English. - Availability for a May/June 2026 internship start, with a 10–12 week commitment. **Key Responsibilities:** - Measure and analyze dangerous capabilities of frontier AI models. - Design and evaluate benchmarks for advanced AI systems. - Develop methods to enhance model reasoning on complex, long-chain tasks. - Construct scalable oversight protocols for human-in-the-loop reasoning validation. - Study model generalization and capability boundaries to drive data-centric improvements. - Research synthetic data generation and hybrid human-machine pipelines for high-quality data scaling. - Optimize production models through retraining, hyperparameter tuning, and post-training solutions for enterprise deployment. **Required Skills:** - Machine learning research, deep learning, or AI safety expertise. - Strong programming skills in Python/JavaScript for model development and experimentation. - Experience with research workflows in natural language processing, computer vision, or multimodal systems. **Required Education & Certifications:** - BS/MS/PhD candidate in Machine Learning, Deep Learning, NLP, or Computer Vision. - Track record of research contributions (publications, open-source projects) in LLMs, AI safety, evaluation, or model alignment. - Prior internships or research roles in ML/LLM fields preferred.

San francisco bay, United states

Hybrid

Fresher

11-11-2025