Latest ML Engineering jobs at Scale AI

Leads architecture, deployment, and evaluation of reliable agentic ML systems for classified and regulated government environments, including geospatial reasoning, retrieval, memory, and shared infrastructure. Requires 8+ years of production ML experience, Staff-level technical leadership, Python, PyTorch, and an active TS clearance.

Owns the architecture, production deployment, evaluation, and improvement of agentic and generative machine learning systems for mission-critical public-sector applications. Requires 5+ years of production ML experience, strong Python and deep learning skills, architectural ownership, and an active TS clearance.

Staff engineer responsible for designing and scaling the infrastructure, execution environments, verifiers, and tooling used to train and evaluate AI agents. Requires 8+ years of software engineering experience, strong Python and distributed-systems expertise, and familiarity with sandboxing, high-throughput systems, and LLM workflows.

Own the operational reliability, governance, and lifecycle maintenance of production AI solutions for public-sector and enterprise customers. The role combines software engineering, MLOps, incident management, automation, model monitoring, and senior client communication.

Builds and deploys retrieval, knowledge representation, and ML platform components for enterprise generative AI systems. The role requires 5+ years of production ML/AI experience, strong Python skills, and expertise in RAG, embeddings, vector indexing, and semantic search.

Leads the design, governance, evaluation, and production delivery of AI systems for public-sector clients. The role requires 7+ years of engineering experience, production AI/ML ownership, expertise in regulated deployments, and the ability to establish technical standards and advise executive stakeholders.

Build scalable, fault-tolerant platforms for serving large language models across research and production environments. The role requires 4+ years of backend systems experience, strong programming skills, and familiarity with LLM serving, containers, cloud infrastructure, and infrastructure as code.

Conduct applied AI research by designing, evaluating, and optimizing machine-learning models and code, with a focus on PyTorch, GPU performance, and generative AI systems. Requires a PhD or postdoctoral degree and 1–3+ years of ML engineering or data science experience.

Builds advanced AI agents and machine-learning solutions for enterprise customers, translating business needs into production systems. Requires strong engineering skills, Python proficiency, cloud experience, and a data-driven approach to model development.

Build and deploy end-to-end AI applications and model evaluation systems for global public sector clients. The role requires 7+ years of engineering experience, production AI/ML experience, and proficiency in modern programming languages and cloud platforms.

Build and evaluate reliable agentic AI systems for high-stakes public-sector applications, spanning applied research, model optimization, safety, and benchmarking. The role requires strong Python and AI infrastructure experience, production engineering rigor, and expertise in LLM evaluation or red-teaming.

Senior engineer building and deploying production AI agents and frontier systems for enterprise customers. Combines latest LLMs, reasoning, retrieval, multi-agent architectures with structured knowledge and traditional ML to solve real business problems across industries. Requires 5+ years experience, strong Python, LLM production experience, and customer-facing skills.

Build and deploy production AI agents and frontier systems for enterprise customers, combining LLMs with retrieval, memory, multi-agent architectures, and traditional ML. Design evaluations, run experiments, ensure reliability/safety, and translate customer problems into scalable AI solutions. Requires 4+ years applied AI/ML experience and strong Python skills.

Senior Machine Learning Engineer building and deploying production GenAI, agentic systems, LLMs, and computer vision models for mission-critical public sector and defense applications at Scale AI. Requires active security clearance, extensive production ML experience, and strong Python/TF/PyTorch skills.

Senior ML Engineer building observability, evaluation frameworks, and improvement loops for production agentic AI systems. Requires 5+ years production ML/LLM experience, strong grounding in agent design or evaluation, and hands-on work taking systems from prototype to scale.

Design domain-specific problems and datasets to evaluate advanced generative AI models, provide expert insights for improvement, and co-author research publications. Requires 5+ years software engineering or equivalent expertise with strong coding in Python, Java, Rust, etc.

Leads development of agentic AI systems for public sector, including guardrails, data processing, and fleet orchestration for federal datasets. Mentors engineers, defines technical strategy, and communicates with stakeholders to ensure reliable, secure solutions.

Leads cross-functional strategic projects in Generative AI to drive multimillion-dollar revenue, owning data labeling operations and product enhancements. Requires 2+ years experience, strong technical skills in SQL/Python, and entrepreneurial mindset.

Staff engineer owns large product areas in enterprise GenAI platform, working across backend, frontend, LLMs, and ML models. Solves scalability challenges with 7+ years experience in Python/JS, Kubernetes, and cloud providers.

Builds and optimizes distributed frameworks for LLM training and inference on Scale's RLXF platform. Collaborates with ML teams to accelerate research, requiring expertise in PyTorch, CUDA, transformers, and large-scale distributed systems.

Build and scale enterprise Generative AI platform, owning large product areas across backend, frontend, LLMs, and ML models. Requires 4+ years experience, proficiency in Python/JavaScript/SQL, Kubernetes, and cloud providers.

Develops synthetic data pipelines, production trace agents, and automated agent-building frameworks for enterprise GenAI. Requires 3+ years LLM production experience, top conference publications, and advanced CS degree.

Designs, builds, and deploys production-ready AI agents using LLMs, tool use, and reasoning for enterprise problems. Requires 5+ years ML experience, Python proficiency, and Bachelor's in CS/ML/AI.

Leads development and optimization of distributed frameworks for LLM post-training, training, and inference. Collaborates with ML teams to enable advanced model development and data curation, requiring expertise in large-scale ML systems and tools like PyTorch and CUDA.

Build and scale full-stack systems for Scale AI's Generative AI Data Engine, owning contributor platform features that power high-impact datasets for LLMs. Requires 5+ years experience with React, TypeScript, Node.js, and strong product sense in a hybrid SF/NY environment.