Lead development and production of ML systems for AI security (detecting prompt injection, jailbreaks, sensitive data exposure, unsafe AI behavior). Responsibilities include model selection and fine-tuning, building reproducible training/evaluation pipelines, improving inference performance and reliability, owning training-data quality and model lifecycle, and establishing responsible ML best practices. Requires 8+ years experience, strong Python and deep learning framework skills, and expertise in distributed training and adversarial evaluation.

DigitalOcean seeks a Principal Engineer, AI/ML Security to own the company's AI security strategy and roadmap, lead adversarial testing and red teaming, review AI product architectures, and build/run ML security tooling and monitoring. Requires 10+ years in cybersecurity with 4–5+ years focused on AI/ML security, deep knowledge of adversarial ML, hands-on experience with Python and Go, and familiarity with frameworks like OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.

Principal engineer role responsible for defining and owning AI security strategy and roadmap, partnering with product and security teams to integrate controls, building and operating adversarial testing, model monitoring, guardrails, and tooling, conducting threat modeling and architecture reviews, and representing AI security to senior leadership.

DigitalOcean seeks a Principal Engineer, AI/ML Security to define and drive AI security strategy and roadmap, perform adversarial ML testing and red teaming, review AI product architectures, build detection/guardrail tooling, and establish AI risk and governance. Requires 10+ years in cybersecurity with 4–5 years focused on AI/ML security, strong Python and Go experience, hands-on adversarial ML knowledge, and familiarity with frameworks like OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and the EU AI Act.

Lead AI/ML security efforts including adversarial testing and red teaming, integrating AI security controls into customer-facing products, building and deploying ML security tooling and guardrails, monitoring models in production, defining AI risk & governance, and representing program-level risk to senior leadership. Requires 10+ years in cybersecurity with 4–5 years focused on AI/ML security, strong Python and Go skills, and hands-on adversarial ML experience.

Role requires owning AI security strategy and roadmap, conducting adversarial ML testing and AI red teaming, defining governance/policies, reviewing AI/ML architectures, and partnering with security and engineering teams. Requires 10+ years in cybersecurity with 4–5 years focused on AI/ML security, strong hands-on experience with adversarial ML, LLM security, model supply-chain risk, and programming in Python and Go.

Hiring a Senior Back-End/MLOps Engineer to develop and maintain backend features (search, ranking, marketplace) and MLOps infrastructure (model deployment pipelines, feature stores, real-time data pipelines, monitoring). Requires 5+ years of software engineering experience and proficiency with at least one of Go, Python, Ruby, or JavaScript/TypeScript; hands-on experience with MLOps tools (e.g., Vertex AI, MLflow, Kubeflow), feature stores, SQL, and cloud platforms (GCP preferred). Remote; employer mentions competitive USD pay.

Seeking a Senior Back-End/MLOps Engineer to build and maintain backend systems and MLOps infrastructure (model deployment pipelines, feature stores, real-time pipelines) for a fast-growing real-estate marketplace. Requires 5+ years experience, strong backend skills (Go/Python/Ruby/JS/TS), SQL, cloud experience (GCP preferred) and hands-on MLOps tools (Vertex AI, MLflow, Kubeflow or equivalent). 100% remote; role based in Colombia (Bogota).

Truelogic seeks a Senior Back-End/MLOps Engineer to join a marketplace team building backend systems for search, ranking, and matching while supporting ML pipelines, model deployment, feature stores, and real-time data infrastructure. Requires 5+ years of software engineering experience, strong backend skills (Go, Python, Ruby, or JavaScript/TypeScript), hands-on MLOps experience (e.g., Vertex AI, MLflow, Kubeflow), feature store experience, strong SQL, and cloud experience (GCP preferred). Position is 100% remote; company headquartered in New York and team is based in Latin America.

Join a marketplace engineering team to build and maintain backend features (search, ranking, matching) and support ML infrastructure including model deployment pipelines, feature stores, real-time data pipelines, and monitoring. Requires 5+ years of software engineering experience, strong backend skills (Go, Python, Ruby, or JS/TS), hands-on MLOps/production ML experience (Vertex AI, MLflow, Kubeflow or equivalent), feature store experience (e.g., Chalk), strong SQL skills, and cloud platform experience (GCP preferred; AWS/Azure acceptable).

Join a marketplace team to build and maintain backend systems powering search, ranking and matching, and to support MLOps infrastructure (model deployment pipelines, feature stores, real-time pipelines, monitoring). Requires 5+ years of software engineering experience, strong backend skills (Go, Python, Ruby, or JavaScript/TypeScript), hands-on MLOps experience (e.g., Vertex AI, MLflow, Kubeflow), feature store experience, strong SQL, and cloud experience (GCP preferred).

Lead architect/engineer responsible for designing, implementing, and productionizing scalable generative AI and agentic AI solutions. Requires 8+ years of experience, deep knowledge of LLMs and Transformers, expert prompt engineering and RAG implementation, strong Python and ML libraries (PyTorch/TensorFlow, Hugging Face, LangChain ecosystem), experience with vector databases and cloud-managed ML services (Azure/AWS), and production experience exposing APIs (FastAPI) and using ORMs. Responsibilities include solution architecture, design reviews, POCs, and collaborating with product and engineering teams to deliver enterprise-grade GenAI systems.

NVIDIA seeks a Senior High Performance AI Engineer to build agentic AI systems across models, multi-agent architectures, runtimes, compilers, and GPUs. The role requires strong C/C++, Rust, and Python skills, GPU/CUDA experience, and at least 4 years of relevant industry or academic experience in AI systems, ML, compilers, or high-performance computing. Responsibilities include building agent architectures, training/evaluation systems, and co-designing software across NVIDIA's hardware and software stack.

Senior-level software engineer responsible for owning technical design and delivery of multi-component AI systems across Mapbox teams. Responsibilities include building evaluation frameworks for non-deterministic systems, shipping LLM-backed features, developing data pipelines (ingestion, conflation, entity resolution, batch/streaming), instrumenting systems for reliability, and participating in on-call rotations. Geospatial and voice pipeline experience, API/SDK design, and MCP familiarity are listed as nice-to-have.

Lead technical direction for the Duo Agent Platform, build reliable orchestration for agents and flows (session lifecycle, tool invocation, concurrency, retries, timeouts), ensure support across GitLab.com, Dedicated, and Self-Managed (including self-hosted models), define evaluation and benchmarking practices, and design governance/safety controls. Role is hands-on, involves cross-team alignment, mentoring, and participating in incident on-call. Requires 8+ years software engineering experience with hands-on LLM/agent experience. Remote in Canada, Poland, United Kingdom, and United States (locations listed in posting).

The Home Depot seeks a Cybersecurity Software Engineer II to build secure, scalable AI-powered security applications. Responsibilities include designing and integrating threat defense capabilities, building agentic AI and RAG systems, integrating MCP, working with cloud services (primarily GCP/Vertex AI), implementing CI/CD and observability, and supporting security operations. Minimum 2+ years' experience; preferred skills include Python, Java, LangChain/agent frameworks, embeddings/vector search, SQL/NoSQL, microservices/APIs, and security concepts (MITRE ATT&CK, authentication/authorization).

Join Quora's Monetization Ads ML team to develop and deploy ads ranking models (CTR/CVR prediction, calibration, user-history modeling). Responsibilities include end-to-end ownership of ML systems: data pipelines, feature engineering, model training, evaluation, and production integration. Minimum 4+ years professional ML software development experience; strong Python and deep learning (PyTorch/TensorFlow) skills; availability during Quora coordination hours (Mon-Fri 9am-3pm PT).

Lead the operational lifecycle of autonomous-vehicle dataset releases: capture and clarify requirements, manage release calendar and priorities, monitor workflows, validate results, communicate status and produce release documentation. Requires 6+ years in ML/data operations or related roles and skills with SQL, data analysis, and cross-team stakeholder coordination.

Sticker Mule seeks an engineer to identify opportunities for autonomous AI agents, build and operate those agents, integrate them with internal and external tools, measure impact and retire ineffective agents, and test new models/tools. Requires experience building autonomous agents, familiarity with Grok, Claude, OpenAI and open-source models, and proficiency in Go, TypeScript, GraphQL, Postgres, and GCP. Fully remote. Salary $150,000–$250,000 USD.

Cloudera is hiring a mid-senior Forward Deployed AI Engineer (Japan-Remote) to prototype and ship full-stack AI and agentic applications, partner directly with strategic customers to move use cases toward production, shape enterprise AI strategy, and codify repeatable solution patterns. Requires 5+ years building and deploying production systems and 2–3 years building generative AI or agentic applications; experience across foundation models, RAG, LLMOps/MLOps, model serving, and enterprise architectures is emphasized.