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We are hiring a hands-on AI expert to shape our intelligent platform, organizing complex real estate data into actionable insights and predictive models that power smarter investment decisions.

Responsibilities
AI/ML Architecture: Design and implement scalable AI systems using models such as LLMs (e.g., OpenAI, Anthropic) and computer vision (e.g., YOLO, CLIP).
MCP Integration: Architect and orchestrate model context flows using MCP or similar frameworks to deliver personalized, context-aware experiences
FinTech Platform Integration: Embed intelligent features into our backend and frontend systems, ensuring seamless UX and robust performance
Hands-On Development: Write production-grade code across Python, TypeScript, and Node.js. Own key modules and guide technical decisions
Team Leadership: Mentor a few developers, set engineering standards, and foster a culture of experimentation and excellence
Data Strategy: Collaborate with product and data teams to define training datasets, feedback loops, and model evaluation pipelines.

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

we are a leading platform for Trust & Safety teams worldwide, leveraging cutting‑edge AI and world‑class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever‑changing threat landscape.
Were seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic.
Key Responsibilities
Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
Develop, deploy and integrate AI solutions and agentic frameworks, creating both command‑line tools and interactive notebooks that support our teams research and workflow automation needs.
Build and manage data pipelines and databases (SQL) for large‑scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
Integrate research into production by implementing the latest generative AI advancements (including white‑box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings
Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end‑to‑end processes for prompt generation, labeling, and response evaluation.

We're looking for an exceptional, hands-on leader-engineer to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team, operating with a high degree of autonomy in an ambiguous, fast-moving environment.
What You'll Do:
Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset.
Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data.
Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems.
Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams.
Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation.

We're looking for a Senior Product Manager to own TokenShift, PointFive's product for finding and cutting wasted AI token spend. This is a chance to define product strategy for a brand-new category, working hands-on with R&D on how AI agents and LLM models actually run, get monitored, and get paid for in production. You'll take TokenShift from early adoption to a core pillar of PointFive's platform, alongside our flagship DeepWaste product.
What You'll Do:
Own the product strategy and roadmap for TokenShift, from discovery through GA and beyond.
Translate a deep technical understanding of how AI agents and LLM workloads run, inference calls, endpoints, agent harnesses and orchestration, into requirements R&D can build against.
Partner with R&D, design, and data science to scope, prioritize, and ship features that surface and reduce AI token waste.
Work directly with enterprise customers and prospects to understand how they deploy AI agents in production and where their cost and visibility gaps are.
Define and track success metrics, adoption, cost savings, detection accuracy, and use them to drive roadmap decisions.
Collaborate with go-to-market teams on positioning, messaging, and launch plans for new capabilities.
Stay current on the landscape: coding agents and harnesses, LLM gateways and routers, AI observability, and endpoint management.
Represent the voice of the customer internally, balancing technical depth with business impact.

we are looking for a AI Data Lead.
As Data Lead, you will own how data gets turned into decisions across the company - and lead the shift from traditional BI into AI-driven BI, powered by agents that surface insight in real time. You'll work closely with one data engineer today, with room to grow the team as scope expands.
You'll define what the data function looks like when AI is embedded in it, not bolted on - from the underlying infrastructure to the dashboards and agents people actually use. The playbook for AI-native BI is still being written, and you'll write a lot of it.
Key Responsibilities
Data Strategy & Ownership:
Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI
Set priorities in partnership with senior leadership
Work closely with a data engineer today, with the option to grow the team as the function scales
AI-Driven BI & Agents:
Drive adoption of AI across data workflows - from automating analyses to agents answering business questions in real time
Own the semantic and metrics layer so every dashboard and every agent reads the same definitions
Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents
Expose our data to agents over MCP so business questions get answered without waiting for a dashboard
Define where AI speeds things up - and where human judgment still has to hold the line
Infrastructure & Analytics:
Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability
Lead complex analytics work, A/B testing, and impact measurement, hands-on
Define evals and quality metrics for AI features and agents - not just A/B tests on dashboards
Cross-functional Collaboration
Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions
Represent the data function to the organization - senior-level storytelling with data

We are looking for a Generative AI Engineer to lead our AI efforts end-to-end - from infrastructure and production systems to internal adoption and cross-team enablement.
You will play a significant role in building the world's first Consumer Therapy AI Product (someone said RAG? But we mean a real one that works in production...).
This is a critical role in a high-growth, fast-paced B2C startup, requiring a leader who can advocate for Engineering requirements, tech-debt and best practices while promoting a product-mindset and putting our customers front and center.

we are looking for a Full-Stack Engineer.
Own features end-to-end across our FastAPI + React/TypeScript stack - the catalog, the seller wizard, payments, admin tooling, and the infrastructure layer we're building next.
What you'll do
Design, build, test, and deploy features across the frontend (React + TypeScript) and the backend (FastAPI + PostgreSQL).
Work on what buyers and sellers touch every day - the catalog, the listing wizard, checkout, the seller dashboard, admin tools.
Help build the next phase: hosting and running sellers' apps on our own infrastructure.
Keep the bar high - tests, code review, security-minded by default.

we are looking for a Process Development Technician.
Responsibilities:
Prepare media and solutions according to established protocols
Assemble and disassemble bioreactors and related equipment
Clean and maintain bioreactors and supporting tools
Calibrate bioreactors to ensure accurate operation
Perform bioreactor sampling as required
Support the Process Development (PD) team with cell maintenance
Accurately document all procedures and experimental activities
Assist in transferring processes to pilot and production scales

we are looking for a QC Specialist.
Responsibilities:
Perform laboratory and environmental tests to assess the quality of raw materials, production areas, processes, and finished products.
Assist the QC Manager in developing and implementing laboratory methods, quality control procedures, and related documentation.
Execute validation protocols for equipment and processes.
Coordinate testing with external contract laboratories.