We are seeking a highly motivated AI Researcher to join our core data Science team. In this role, you will be at the forefront of tackling complex, high-impact business challenges by leveraging cutting-edge GenAI technologies, advanced AI research, and classical Machine Learning and statistical modeling. You will not just be building models; you will be driving research from ideation to production. We are looking for a true self-learner, someone who thrives in an environment that demands both a strong sense of ownership over your deliverables and deep collaboration. You will work closely with fellow researchers, product managers, and software developers to translate abstract business problems into scalable data -driven solutions. If you are passionate about staying ahead of the AI curve, building agentic workflows, and proactively driving your research initiatives forward within a collaborative team structure, this is the perfect role for you.
What You Will Do: End-to-End Research & Ownership: Lead targeted research projects from initial hypothesis through to production-ready solutions. Take strong ownership of your work's performance and partner with engineering to ensure successful, scalable integration Applied AI Research & Integration: Lead research into LLMs, agentic systems, and modern AI methods, then design and build the workflows that bring them into our ecosystem. LLM Evaluation & Optimization: Contribute to and establish rigorous evaluation frameworks for LLMs to ensure accuracy, safety, and business alignment in practical applications. Cross-Functional Collaboration: Act as a bridge between data, engineering, and product. Work with Developers to ensure seamless integration of ML features into the core product. Continuous Innovation: Act as an internal advocate for emerging AI research and methodologies. Continuously read, experiment, and implement state-of-the-art techniques to advance our research agenda and accelerate research velocity.

Position Intro:
Earnix is the first AI company purpose-built for insurance decisioning, providing the industry with the intelligence, governance, and decisioning agility to drive profitable growth, improve resilience, and operate with speed and precision in a rapidly changing risk environment. A trusted provider of production-grade AI and decisioning technology, Earnix builds on more than 25 years of experience in artificial intelligence risk, pricing, rating, analytics, and decisioning. Earnix brings vertical AI into the workflows and decisions that shape insurance performance across insurers pricing, underwriting, claims, customer engagement, retention, and other insurers high-value insurance moments. Earnixs AIOS enables insurers to orchestrate intelligence across the insurance decision lifecycle and drive governed, Real-Time decisions that deliver measurable business outcomes. Earnix is headquartered in Boston, MA and has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

We are seeking a highly motivated AI Researcher to join our core Data Science team. In this role, you will be at the forefront of tackling complex, high-impact business challenges by leveraging cutting-edge GenAI technologies, advanced AI research, and classical machine learning and statistical modeling.
You will not just be building models; you will be driving research from ideation to production. We are looking for a true self-learner, someone who thrives in an environment that demands both a strong sense of ownership over your deliverables and deep collaboration. You will work closely with fellow researchers, product managers, and software developers to translate abstract business problems into scalable data-driven solutions.
If you are passionate about staying ahead of the AI curve, building agentic workflows, and proactively driving your research initiatives forward within a collaborative team structure, this is the perfect role for you.
What You Will Do:
End-to-End Research & Ownership: Lead targeted research projects from initial hypothesis through to production-ready solutions. Take strong ownership of your work's performance and partner with engineering to ensure successful, scalable integration
Applied AI Research & Integration: Lead research into LLMs, agentic systems, and modern AI methods, then design and build the workflows that bring them into our ecosystem.
LLM Evaluation & Optimization: Contribute to and establish rigorous evaluation frameworks for LLMs to ensure accuracy, safety, and business alignment in practical applications.
Cross-Functional Collaboration: Act as a bridge between data, engineering, and product. Work with Developers to ensure seamless integration of ML features into the core product.
Continuous Innovation: Act as an internal advocate for emerging AI research and methodologies. Continuously read, experiment, and implement state-of-the-art techniques to advance our research agenda and accelerate research velocity.

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 hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind Alice'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 Alice'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.



About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative an

we are looking for a Senior Data Analyst.
The Custom Feeds team turns Placer's data into production-grade bespoke data products for our largest customers - tailored to specific business questions and shipped on a recurring basis. We're looking for a Senior Data Analyst who is both a pipeline builder and a data researcher. You'll own custom recurring feeds end to end - from methodology for new metrics, through pipeline design, to final acceptance before delivery. You'll lead conversations with internal stakeholders (US-based customer-facing teams and colleagues across R&D) and help generalize recurring logic into reusable models, metrics and packages the whole team builds on. Ideal for a rigorous, independent thinker looking for a delivery-oriented role where impact is tangible.
Responsibilities:
Own custom feeds from requirements through delivery and ongoing maintenance
Develop methodologies and acceptance criteria for new metrics
Build reproducible, tested production pipelines in PySpark on Databricks, orchestrated with Airflow and Terraform
Partner with Solution Engineers and customer-facing teams on timelines, methodology and customer feedback
Build reusable components and packages; collaborate with R&D and Data Science to reuse existing datasets, models and products - and make your work reusable by others

We are looking for an exceptionally strong software engineer to join our Technology organization. You will be part of a business-facing team responsible for building and evolving the core systems that power our Quant strategies. This is an AI-forward team: large language models (LLMs) and AI agents are part of our daily workflow - from writing and reviewing code, to automating operational toil, to building internal copilots and agentic tools that the whole team relies on. You won't just use AI to move faster; you'll help shape how it's applied across our engineering practice.

Design and build data pipelines and the data layer.
Develop and maintain the computational frameworks and infrastructure that run our quantitative strategies at scale.
Implement and enhance quant-related software systems for data, research, portfolio construction, and trading.
Work closely with Researchers, and Quants as a hands-on engineering partner, helping them turn ideas into robust production solutions.
Gain exposure to the full lifecycle of the systematic/quant business, from data ingestion through research, implementation.
Build and integrate AI-powered tooling - LLM agents, copilots, and automation - into engineering and research workflows.
Use AI coding assistants and agentic developer tools to ship higher-quality software faster.

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within us as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

Alice is hiring a Senior Software Developer to lead the development of our internal malware research platform. This is a senior, hands-on role with end-to-end ownership of development and delivery. You'll be the technical authority — setting code-quality standards, making the architecture calls, and mentoring the developer team. What makes this role different is who you build for. Our users are our malware researchers, and they use the tool every day. Your job is to sit beside them, learn how they actually work, surface the heuristics and edge cases they carry in their heads, and build agentic tooling that compounds their productivity. The bar isn't "does it ship" — it's "do the researchers reach for it every day." Success is measured in researcher adoption and time saved, not features merged. Agentic workflows are core to how we build. You should be fluent using them and confident designing systems where agents run in production — with clear judgment about where an agent earns its keep versus where deterministic code or a human-in-the-loop is the right call. What You'll Do Lead development and delivery
* Own technical execution end-to-end: implementation, code review, and release.
* Translate research workflows and feature requests into well-scoped tasks with realistic, risk-aware estimates the team can plan against.
* Manage day-to-day execution: unblock people, sequence work, catch problems early.
* Set and defend the technical bar: review rigor, testing discipline, documentation, architectural consistency. Partner with the researchers — and amplify them
* Embed with malware researchers to understand their workflow and capture the tacit knowledge and edge cases no spec ever wrote down.
* Translate that knowledge into reliable agentic tooling — and know when an agent is confidently wrong before it ever reaches a researcher.
* Spend roughly 5–10% of your time doing actual malware research (with structured onboarding) to stay close to how the tool is used.
* Be willing to tell a researcher when a proposed workflow won't automate well — and explain why. Be the technical authority and mentor
* Make the hard architecture and design trade-off calls.
* Mentor through code review, pairing, and design discussions. Raise the level of everyone around you.
* Dive deep on the critical, difficult features and bug fixes yourself.
* Design agentic workflows into the architecture from the start, and build the evaluations and guardrails that keep them trustworthy.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!