Dragos is on a relentless mission to defend industrial organizations that provide us with the necessities of modern civilization; running water, functioning electricity, and safe industrial working environments. As the market leader in ICS/OT Cybersecurity, we are dedicated to arming our customers with best-in-class technology, threat intelligence, and services to protect their systems as effectively and efficiently as possible. We’re a remote-first culture with operations in North America, Europe, the Middle East, and APAC. We’re looking for mission-oriented teammates who embody our core values of authenticity, transparency, and trust. Are you ready to make a difference? Come join a mission that can save the world! About the Role : We're seeking an experienced Staff Machine Learning Engineer to join our Engineering team. In this role, you'll drive the design and implementation of production machine learning systems within the Dragos platform. Working closely with Data Scientists, Data Engineers, and product teams, you'll build and deploy AI/ML capabilities that enhance threat detection, automate security analysis, and deliver actionable intelligence for Industrial Control System (ICS) and Operational Technology (OT) cybersecurity applications. Responsibilities : Design and implement production-grade machine learning systems that expand Dragos product capabilities, with consideration for both cloud and resource-constrained on-premises environments. Build and optimize ML model architectures for ICS/OT cybersecurity use cases, including threat detection, asset classification, behavioral analysis, anomaly detection, and natural language processing systems. Develop robust data pipelines and ML workflows that integrate with existing data infrastructure, supporting both real-time and batch processing requirements. Qualifications : 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments. Strong software engineering foundation with expertise in Python and SQL as well as experience with at least one additional language (Go, Rust, Java, or JVM-family languages). Demonstrated experience building and deploying ML systems using modern frameworks and libraries (scikit-learn, PyTorch, TensorFlow, HuggingFace, or similar). Experience with LLMs, retrieval-augmented generation (RAG), or advanced NLP techniques is beneficial. Proven track record implementing ML solutions such as classification systems, time series analysis, anomaly detection, or NLP applications that deliver measurable business impact. Experience with MLOps practices, including model versioning, monitoring, pipeline orchestration, and deployment in high-reliability environments. Familiarity with data engineering concepts, including data pipelines, stream processing, message queuing, and working with medium-to-large scale datasets. Knowledge of containerized deployment solutions and cloud-native architectures. Strong communication skills with the ability to explain technical concepts to diverse stakeholders and collaborate effectively across teams. Cybersecurity domain knowledge, particularly in threat detection, threat intelligence, or ICS/OT operations, is a strong plus. Compensation : Salary: $225,000 Competitive Equity Package Comprehensive Benefits Plan Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform. We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users. What you’ll do As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently. You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account. Responsibilities Our team operates fluidly and here are some problems you may tackle: Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence. Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale. Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard. Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc. Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability. Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast. Who you are Minimum requirements 5+ years in AI/ML and backend engineering. Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc. Proficient in Python (Ruby is a plus); strong distributed systems fundamentals. Experience working closely with product management, design, other engineers, and other cross-functional partners. Preferred qualifications Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design. Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements. Track record building ML platforms, especially those that enable multiple teams to collaborate together. Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity. Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you.

Post Producer: (Feature Film) Location: NYC/LA/London Employment: Contract About Wonder Studios We are an AI native creative studio building performance centric, productionised pipelines for ambitious short and feature projects. We combine traditional VFX craft with emerging AI-driven techniques to reduce cost, speed up iteration and preserve high quality finish. Role summary We are hiring a senior Post Producer to lead bidding, budgeting and workflow design for a VFX-heavy feature films. The role will define a repeatable, productionised approach that blends AI-driven processes with conventional comp, roto, 3D and cleanup. You will own the commercial and operational delivery model for VFX across pre-production and post. Key responsibilities Lead VFX bid and budget creation for feature film scope • Break down sequences and shots, produce detailed shot lists and task lists suitable for vendor and internal costing • Translate creative VFX requirements into realistic vendor scopes, staffing plans and delivery milestones Must have Significant experience bidding and producing VFX for feature films with demonstrable credits on VFX heavy features • Strong track record producing accurate, defensible feature-level VFX budgets and vendor bids • Hands on experience with shot breakdowns, vendor costing and creating productionised workflows for complex VFX projects • Proven vendor management and negotiation experience across comp, roto, 3D and cleanup vendors • Practical familiarity with post tracking tools such as ShotGrid, Nuke, Maya, Houdini or equivalent pipelines • Excellent stakeholder communication and the ability to present budgets and workflow proposals to producers and financiers Nice to have Practical understanding of AI-enabled workflows and tools used in image and video generation, enhancement or automation • Experience integrating AI processes into a VFX pipeline • Experience working with distributed editorial and VFX teams, remote review platforms and high throughput delivery models • Experience with cost per minute or cost per shot pricing frameworks for features

• Develop and deploy AI chatbot/agent solutions for enterprise use cases • Integrate LLM-based agents with structured and unstructured enterprise data • Connect chat interfaces to SQL/enterprise databases and internal APIs • Build and integrate machine learning models (prediction, classification, clustering, etc.) • Perform data preprocessing, feature engineering, and model evaluation • Integrate ML outputs into chatbot or workflow interfaces • Support data pipeline development and automation • Collaborate with internal team and occasionally clients to understand requirements • Document model logic, workflows, and implementation details