The role

Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale.

• Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.                                                                                
• Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning.

• Deep expertise in modern deep learning for language processing and generation

• Experience with training large models on multiple computational nodes

• Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)

• Strong software engineering skills (we mostly use Python)

• Deep experience with modern deep learning frameworks (we use JAX)

• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

• Strong communication and leadership abilities

Nice to have:

• Previous experience working with language models or other similar NLP technologies.

• Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization

• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.

• Strong engineering skills, including experience in developing large distributed systems or high-load web services.

• Open-source projects that showcase your engineering prowess

• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

The role

This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:

• investigating how test-time guided search can be used to build more powerful agents;
• dramatically scaling task data collection to power reinforcement learning for SWE agents;
• maximizing efficiency of LLM training on agentic trajectories.

One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models.

This role will require expertise in distributed systems to build large-scale LLM training platform.

Your responsibilities will include: 

• Designing and developing LLM training platform.
• Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability.
• Improving job scheduling strategies to minimize resource fragmentation. 

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

The role 

We are looking for a Senior Product Manager to join our Agentic Search team, building the search and retrieval infrastructure that powers AI agents and LLM-based applications at scale.

This is a hands-on IC role with real ownership. You will take full end-to-end responsibility over a core product area, from defining strategy through shipping and iterating based on real usage data. You will work within a small PM team reporting to the Director of Product, alongside engineering, design, and go-to-market, shaping how AI agents discover, retrieve, and act on web information in real time.

The product serves both a developer-facing PLG motion and a growing enterprise customer base, so you will need to be equally comfortable digging into API design and search quality as you are running customer discovery calls and informing competitive positioning. We are looking for someone who can operate as a senior strategic partner, not just an executor, and who has the potential to grow into a principal-level PM over time.

You’re welcome to work hybrid from Tel Aviv, Israel.

Your responsibilities will include: 

• Own a core product area end-to-end: strategy, roadmap, execution, and iteration based on real usage signals and customer feedback.
• Drive search quality and relevance improvements by working closely with engineering and research to define evaluation frameworks, benchmarks, and release criteria.
• Engage directly with enterprise customers and developer users to validate ideas, understand pain points, and shape product-market fit across both PLG and enterprise motions.
• Monitor the competitive landscape in agentic search and AI-powered retrieval, identifying shifts, threats, and opportunities that should inform product decisions.
• Collaborate with go-to-market teams (sales, solutions, growth) to ensure product positioning, ICP definitions, and enablement materials reflect product reality.
• Contribute to product strategy as a senior voice on a small, high-impact team, challenging assumptions and bringing independent judgment to key decisions.
• Lead product experiments and rapid iteration cycles, moving from hypothesis to prototype to production with clear success criteria.

We expect you to have: 

• 5+ years of product management experience, with a meaningful portion in developer tools, API platforms, or search and retrieval infrastructure.
• Track record of shipping products in fast-moving markets, working closely with engineering and design from concept through launch and iteration.
• Strong understanding of LLMs, AI agents, and how search and retrieval systems fit into agentic workflows. Hands-on technical background is a strong plus.
• Degree in computer science, engineering, or a related field, with the ability to engage deeply with technical architecture and tradeoffs.
• Comfortable operating in ambiguity: you can context-switch between strategic thinking and tactical execution without losing the thread.
• Proven ability to influence cross-functional stakeholders and drive alignment without formal authority.
• Excellent written and verbal communication: you can explain technical concepts clearly to both engineers and business stakeholders.

It will be an added bonus if you have: 

• Experience in search, information retrieval, NLP, or adjacent domains.
• Background in API-first or developer-platform businesses with both PLG and enterprise motions.
• Leadership experience in a high-growth technology company, especially post-acquisition or startup-within-a-larger-org environments.
• People management or mentoring experience (building the skills of other PMs).

About the Product 

Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises. 

We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs. 

Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases. 

 About the Team 

We are a fast-growing, distributed team of engineers and product professionals based primarily in Europe. The team brings together strong backend, frontend, product, and business expertise, with a shared focus on building impactful, scalable systems. 

While we initially started without deep specialisation in AI/ML, the team has rapidly grown into the  space—demonstrating strong ownership, curiosity, and the ability to tackle complex technical challenges. 

Technology & Environment 

Our work is deeply integrated with a broader cloud and infrastructure ecosystem. We primarily use Go and Python to build and scale backend systems and collaborate closely with teams focused on areas such as infrastructure, observability, billing, and AI research. 

The platform continues to evolve from a lightweight integration layer into a more comprehensive system, including custom infrastructure, optimisations, and deeper control over performance and reliability. 

What We’re Working On 

• Scaling distributed systems: Expanding our platform to handle significantly increased workloads while maintaining performance and reliability  

• Improving reliability: Enhancing system stability and uptime to meet enterprise-grade expectations  

• Optimising AI performance: Continuously adapting to new models, hardware, and runtime improvements  

• Expanding platform capabilities: Building beyond inference into broader AI infrastructure, including data pipelines, customization, and advanced usage features  

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

Why It’s Interesting 

This is an opportunity to work at the intersection of distributed systems, cloud infrastructure, and applied AI, tackling real-world scalability challenges and shaping how companies adopt AI in production environments. 

Hi there! We are Testlio, a global testing company. We are looking for people in Israel to participate in a paid moderated user research session about a financial/payment app experience.

No technical experience necessary. We are looking for everyday people to share honest feedback while completing real tasks in the app and speaking live with a Testlio researcher during the session.

Compensation: $100 USD for approximately 1 hour of your time

During the Live Research Session, Participants will:

• Meet 1:1 with a Testlio researcher in a live video call
• Create a new account on a financial app
• Complete identity verification steps (uploading ID documents)
• Connect a real bank account
• Transfer a small amount of money (fully reimbursed)
• Share thoughts, reactions, and feedback out loud throughout the experience

The session will include screen, audio, and video recording for research analysis purposes. Any sensitive or personal information will be blurred/redacted. A consent form will be shared before participating.

Requirements

• Availability: Must be available for a 1-hour live video session between May 11 – May 15
• Age: Must be at least 18 years old
• Location: Must be physically located in Israel and be an Israeli citizen
• Language: Speak both Hebrew and English
• Must have an Israeli phone number
• Must have a bank account with any of the below banks:
  • Bank Hapoalim
  • Bank Leumi
  • Bank Mizrahi
• Must have at least 2 valid IDs available (Teudat Zehut, passport, or driver’s license)
• Devices needed: iOS or Android Mobile Phone

No research or software testing experience is needed. We are specifically looking for natural, honest feedback from real people.

Participants Must Be Comfortable:

• Joining a live video call with a researcher
• Verbally sharing feedback while using the app
• Completing identity verification steps
• Linking a real bank account
• Sending a small transaction (that will be reimbursed under 24 hours)

How to start?

Once you are ready, please fill out the application. Those who meet the requirements will receive further information to participate in this paid testing opportunity.

If you have any questions or need help, please contact Opportunities@testlio.com using the code ISRAELTEST in the Subject line/email body so we can quickly identify your request.

#LI-REMOTE

Wolt is a Helsinki-based technology company with a mission to bring joy, simplicity, and earnings to the neighborhoods of the world. Wolt develops a local commerce platform that connects people looking to order food, groceries, and other goods with people interested in selling and delivering them.

Wolt was founded in 2014 and joined forces with DoorDash (NASDAQ: DASH) in 2022. Together, we operate in more than 30 countries today, 28 of which are with the Wolt product and brand.

Wolt launched in Israel in November 2018 with 26 restaurants in Tel Aviv. Today, Wolt covers most of Israel’s population across 300+ cities and towns, from Kiryat Shmona to Eilat. Our platform offers an additional sales channel to more than 10,000 Israeli merchants and provides a flexible earnings opportunity to over 20,000 active courier partners. Our team has grown from a few people in a small office to over 1,500 employees across nationwide locations — and we’re just getting started.

As a Courier Experience Specialist at Wolt Israel, you will play a strategic role in shaping the end-to-end experience of our courier partners - from onboarding and engagement to satisfaction and retention. You will leverage data, insights, and creative thinking to build scalable programs and initiatives that ensure couriers feel valued, supported, and connected to our mission.

This is not just an operational role - it’s an opportunity to influence how Wolt designs and delivers the courier experience nationwide, and to be the professional authority for courier engagement, social media strategy, and community building. You will collaborate cross-functionally with Operations, Product, Support, and Marketing teams to continuously enhance every digital and physical touchpoint for our couriers.

Key Responsibilities

Experience & Community Startegy

• Own, design, and execute large-scale projects and initiatives that improve the overall courier journey, from app usability to well-being programs, with a measurable impact on engagement and satisfaction.
• Define and execute the social media and community strategy for our couriers. Build, scale, and manage a thriving, inclusive digital community.
• Establish and own the official "Tone of Voice" for all courier-facing communications (in-app, newsletters, social media, website), ensuring it is authentic, effective, and builds trust.
• Manage and optimize the courier website and other digital platforms, maximizing their potential as communication and engagement hubs.

Insights & Analytics

• Analyze complex data from all sources (surveys, social media sentiment, roundtables, operational data) to identify friction points and transform insights into concrete initiatives.
• Act as the "voice of the courier" to the Product team, translating qualitative feedback and data analysis into clear recommendations to influence the product roadmap.
• Track key metrics (NPS, retention, social engagement), providing regular reports and strategic recommendations to leadership.

Engagement & Operations

• Plan and execute impactful events, competitions, workshops, and recognition programs that strengthen the sense of belonging.
• Partner with the Support team to define and maintain the quality of service, ensuring new features, procedures, and communications are rolled out effectively.
• Act as a trusted representative for courier needs, serving as the subject-matter expert for the courier experience across the organization.

Qualifications

Experience:

• 4+ years of proven experience in a strategic role focused on Community Management, Social Media Management, or Customer/User Experience, ideally in a fast-paced tech or gig-economy company.
• Must have experience in building and scaling digital communities from the ground up, with a deep understanding of social media platforms and strategy.
• Demonstrated success in managing large-scale, cross-functional projects from conception to completion.
• Proven ability to use data and analytics to build business cases and influence a product roadmap.
• Experience in defining a brand's Tone of Voice and creating multi-channel communication strategies.

Skills:

• Exceptional analytical skills: The ability to dive deep into data (qualitative and quantitative), find the "so what," and translate it into measurable impact.
• Creative and strategic thinker: You don't just follow a playbook; you invent the playbook and know how to create a new language with users.
• Assertive and influential: Excellent communication skills (fluent Hebrew and English) with the ability to build consensus, present clearly to leadership, and drive change.
• Grounded and hands-on: A "roll-up-your-sleeves" mentality, passionate about "living the field," understanding the end-user, and not being afraid of hard work.

Personal Qualities:

• A natural leader and professional authority: You inspire confidence, bring new knowledge, and can "level up" the expertise of the entire team.
• Highly proactive and solution-oriented: You don't wait for problems; you identify them, propose solutions, and own the results.
• High empathy balanced with a strong, data-driven, and results-oriented mindset.

Additional Information

If you thrive in a fast-paced, high-impact environment and want to make a real difference in the lives of thousands of people across Israel, we’d love to meet you.
Join us! and help build the most trusted, empowered, and happy courier community in Israel.

So, what’s the role all about?

As AI Quality Architect, you are the person who makes quality native to the agentic SDLC. You design the systems, standards, and intelligence layers that ensure every stage of an AI-accelerated pipeline — from requirement ingestion to autonomous deployment — is observable, trustworthy, and continuously improving. You don't retrofit testing onto AI workflows; you architect quality into them from the ground up.

How will you make an impact?  

Agentic Quality Architecture

• Design the end-to-end quality architecture for agentic SDLC pipelines — spanning requirement analysis, code generation, test creation, execution, triage, and release gates
• Define how quality agents are orchestrated: which decisions they own autonomously, which require human-in-the-loop checkpoints, and how confidence thresholds govern both
• Architect multi-agent quality workflows: requirement validation agents, test generation agents, failure triage agents, and regression analysis agents working in coordinated pipelines
• Establish trust and verification models for agent-produced artifacts — test code, assertions, coverage reports, and defect analyses must all be auditable and traceable
• Own the architectural patterns for quality feedback loops between agents: how a deployment agent learns from a triage agent's findings, and how that signal improves future generation

AI-Native Test Engineering Platform

• Design and own the LLM-powered test generation platform — from natural language requirement ingestion to executable, maintainable test output
• Architect the evaluation harness that continuously measures test generation quality: coverage delta, false-positive rates, assertion accuracy, and maintenance burden over time
• Build the self-healing test infrastructure layer — agents that detect broken selectors, drifted APIs, or changed behaviors and propose or apply fixes autonomously
• Define the prompt engineering standards, context injection patterns, and RAG architectures that ground test generation agents in real codebase context
• Architect test artifact governance: versioning, ownership attribution (human vs. agent), rollback capability, and confidence scoring for every generated artifact

Quality Gates in Autonomous Pipelines

• Design intelligent, adaptive quality gates that operate at the speed of agentic CI/CD — gates that reason about risk, not just pass/fail thresholds
• Build risk-scoring models that dynamically adjust gate strictness based on change scope, code origin (human vs. AI-generated), historical failure patterns, and deployment context
• Architect the observability layer for agentic pipelines: what signals indicate a pipeline agent is making poor quality decisions, and how are those signals surfaced in real time
• Define the integration patterns between quality gates and orchestration platforms (LangChain, LlamaIndex, custom agent frameworks) used across the engineering org
• Establish rollback and circuit-breaker patterns for autonomous deployments triggered by quality signal degradation

AI Model & Agent Validation

• Build behavioral testing frameworks for validating AI agents and LLM-powered features in production — testing non-deterministic outputs with statistical rigor
• Design evaluation benchmarks for internal AI tooling: measuring agent task completion accuracy, hallucination rates, context retention, and decision quality over time
• Architect drift detection systems that identify when agent behavior changes between model versions, prompt updates, or context window shifts
• Define adversarial and edge-case testing methodologies for AI features: prompt injection resistance, boundary condition handling, and graceful degradation under distribution shift
• Partner with ML platform and data science teams to establish quality acceptance criteria for every model and agent promoted to production

Have you got what it takes?

• 12+ years in software engineering with strong depth across both development and quality engineering
• 4+ years as a hands-on principal architect or distinguished engineer with cross-org technical scope
• Demonstrated experience designing quality infrastructure used at scale — 50+ engineers, high-velocity pipelines, enterprise SLAs
• Direct production experience building or operating systems that incorporate LLMs or AI agents — not evaluations, but shipped systems
• Background in large-scale CI/CD architecture and the performance engineering domain
• Enterprise SaaS or platform engineering background; familiarity with regulated, high-uptime environments strongly preferred

Agentic AI & LLM Proficiency

• Deep, hands-on understanding of agentic AI patterns: tool use, multi-agent orchestration, planning loops, memory architectures, and human-in-the-loop design
• Expert-level prompt engineering including chain-of-thought, few-shot, RAG, and structured output techniques applied to code and test generation
• Experience designing evaluation harnesses for non-deterministic AI systems — statistical confidence, behavioral consistency, and regression detection
• Familiarity with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or equivalents) and their tradeoffs in production quality pipelines

Technical Depth

• Expert in Python and TypeScript; proficient in at least one compiled language (Java, Go, C#)

• Strong CI/CD architecture skills: Jenkins, GitHub Actions, pipeline-as-code, artifact management

Leadership & Influence

• Proven ability to drive technical consensus and architectural adoption across multiple teams without direct authority
• Exceptional written communication — your ADRs, RFCs, and design docs set the standard others follow
• Effective technical mentor to senior and staff engineers; you expand the thinking of those around you
• Comfortable and credible presenting to VP and C-level stakeholders; you make complex architecture legible to executives

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 10833
Reporting into: Senior Director, Engineering, CX
Role Type: Individual Contributor

#LI-Hybrid

As a Machine Learning Engineer at MyHeritage, you will play a crucial role in developing and implementing machine learning models that drive our products and user experiences. You will have a significant impact on our large and growing user base by leveraging the latest AI technologies to solve challenging problems at scale. This is a unique opportunity to join a forward-thinking team that is passionate about innovation, data, and machine learning.

What you’ll do

• Design, develop, and deploy machine learning models for various business needs.
• Collaborate with cross-functional teams, product managers, and software engineers, to integrate ML solutions into production systems.
• Experiment with and iterate on model architectures to improve accuracy, efficiency, and scalability.
• Work with large datasets to preprocess, clean, and extract meaningful features for model training.
• Utilize MLOps best practices to automate and streamline the development lifecycle of ML models.
• Monitor model performance and fine-tune for optimization.
• Stay updated with the latest research and advancements in machine learning and AI.

What you bring

Technical skills:

• Strong foundation in machine learning techniques such as supervised and unsupervised learning, deep learning, and vision/NLP experience.
• Proficiency in Python, along with popular ML libraries and frameworks such as PyTorch, Scikit-Learn, pandas, NumPy, SciPy, TensorFlow.
• Experience with data preprocessing and feature engineering for structured and unstructured data.
• Knowledge of model deployment and serving, using tools like Docker, Kubernetes, or cloud-based services (AWS, GCP, Azure).
• Familiarity with MLOps tools for automation and monitoring (e.g., MLFlow, ClearML).
• Experience with SQL for data extraction and analysis (optional).

Experience:

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
• 7+ years of experience in software development, including at least 3 years of experience in the machine learning domains.
• Experience working in a B2C company or a similar high-paced environment is an advantage.
• Proven track record of implementing impactful machine learning solutions in production.

Core attributes

• Strong analytical mindset, with the ability to tackle complex problems with creativity and efficiency.
• Excellent communication skills for conveying technical ideas to both technical and non-technical stakeholders.
• High level of attention to detail and quality in your work.
• Ability to work effectively in a team environment, while also being a self-starter when working independently.
• Curious and eager to keep learning about the latest trends in AI and machine learning.
• Comfortable in a fast-paced, dynamic work environment with changing priorities.

 About MyHeritage

MyHeritage is the leading global discovery platform for exploring family history. With billions of historical records and family tree profiles, and with sophisticated matching technologies that work across all its assets, MyHeritage gives users the joy of discovering their past and empowering their future. MyHeritage is the most popular DNA test and family history service in Europe. Since 2020, MyHeritage is also home to the world’s most advanced AI technologies for repairing, enhancing, colorizing, and animating historical photos. Learn more at www.myheritage.com. See what it’s like to work at MyHeritage on www.glassdoor.com.

Benefits at MyHeritage

Our employees enjoy a range of benefits to enhance work-life balance and well-being:

• Hybrid work model
• Modern, beautiful office in Or Yehuda with shuttle service from Tel Aviv and employee parking (for our Or Yehuda employees)
• On-site gym and pilates classes
• Dog-friendly office
• Well-stocked kitchens and a monthly meal allowance 
• Fully funded supplemental health insurance

#LI-Hybrid

Role Overview

Astera Labs is establishing a strategic R&D center in Israel to drive the development of complex semiconductor chips that solve the critical 'data bottlenecks' enabling the future of AI at scale. As we expand our presence in Israel, we're seeking a visionary Design Verification Student to help build our local engineering powerhouse from the ground up. This is a unique opportunity to take on meaningful product ownership in a new site, designing complex solutions that sit at the heart of our most ambitious connectivity projects.

As a Design Verification Student, you will be at the forefront of quality, learning how to ensure that the chips powering the world's largest AI clusters are bug-free and robust.
This isn't just about running tests - it’s an opportunity to learn advanced verification methodologies (UVM/SystemVerilog) alongside world-class engineers. You will support the development of sophisticated testbenches and help verify high-performance digital blocks that sit at the heart of AI infrastructure.

Key Responsibilities

• Assist in building and maintaining System Verilog/UVM-based testbenches, including monitors, checkers, and functional coverage models
• Run simulations, analyze failures, and work with the design team to debug and resolve RTL issues
• Help define and implement functional coverage and assertions to ensure all "corner cases" of the design are tested
• Utilize and improve scripting (Python/Tcl) to streamline verification flows and result reporting
• Partner with Design Engineers to understand block specifications and ensure the verification plan matches the design intent

Basic Qualifications

• Pursuing a Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related technical field
• Ability to work at least 2 days a week at our Haifa/Tel Aviv center
• Strong understanding of Digital Logic and at least one programming language (C/C++ or Python)
• Basic familiarity with Verilog or SystemVerilog from academic projects or lab work
• A natural curiosity for "breaking things" and finding bugs, with a strong attention to detail
• Fluent in Hebrew and English with the ability to work effectively in a team environment

Preferred Qualifications

• Completed courses in VLSI, Digital Systems, or Computer Architecture
• Proficiency in Python, Perl, or Tcl
• Any prior exposure to UVM/OVM or constrained-random verification is a major plus
• Basic understanding of protocols like PCIe, Ethernet, or DDR

Realize your potential by joining the leading performance-driven advertising company!  

Taboola, the world’s largest content recommendation platform, is hiring a Senior Programmatic Account Manager for our TLV Office. In this role, you will be directly responsible for managing a book of business of tier-1 clients, identifying and executing upsell & optimization opportunities at scale. 

You will excel in this role if you enjoy working in a highly technological & analytical environment, and love developing rock-solid relationships with international clients.

 To thrive in this role, you'll need:

• B.A / BSc degree
• 5+ years of professional client facing experience in the Programmatic / Performance Marketing space - a must
• Ability to provide world-class client service while keeping a focus on growing revenues
• Strong analytical skills - proficient in working with Excel advanced functions. Familiarity with BI platforms such as Tableau / QlikSense / Looker - an advantage
• Love for data-driven decision making - ability to monitor, A/B test and identify trends in data to generate action items and insights
• Excited about complex analytical challenges and enjoy solving them
• Fluency in English
• You are highly motivated, super proactive and dedicated person
• You are a natural collaborator, able to work with multiple teams to reach a common goal
• You are a quick learner with great attention to details and multi-tasking capabilities

Bonus points if you have:

• Experience working with programmatic platforms (SSPs & DSPs) on different types of integrations, preferably OpenRTB
• A love for the challenge of upselling and relationship building with large, international B2B organizations
• Familiarity with different AI tools and the ambition to adopt LLM based functions to improve productivity

How you’ll make an impact:

• Manage a book of business of programmatic partners - understand client strategic objectives & KPIs in order to be able to intelligently identify and execute opportunities, upsell effectively and grow the overall partnership
• Monitor, troubleshoot and optimize performance for different types of client integrations and activities
• Use data analytics tools (Tableau, QlikSense, Excel, etc.) on a daily basis to draw business conclusions and identify opportunities for growth
• Routinely meet & have weekly calls with your clients to share insights & potential initiatives, and review overall performance - backed by data
• Successfully build and maintain close relationships with key people in your book-of-business. Strengthen partnerships with clients and influence their business strategy & decision making
• Develop and execute long-term account plans and conduct QBR (quarterly business review) meetings with strategic clients
• Work very closely with Product Management- as well as other internal teams - to increase client engagement by building new features / improving products based on clients feedback, as well as troubling technical issues

Why Taboola?

If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:

• Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.
• Well-being: Enjoy comprehensive benefits (health, etc.), a fully stocked kitchen, and location-specific perks (gym, parking).
• Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired.
• Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, Expedia and Honda.

Ready to realize your potential?

Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.

Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog.

About Taboola

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.

Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.

#LI-GG1

#LI-Hybrid

Realize your potential by joining the leading performance-driven advertising company!  

Taboola, the world’s largest content recommendation platform, is hiring a Senior Performance Account Manager for our TLV Office. In this role, you will be directly responsible for managing a book of business of tier-1 clients, identifying and executing upsell & optimization opportunities at scale. 

You will excel in this role if you enjoy working in a highly technological & analytical environment, and love developing rock-solid relationships with international clients.

 To thrive in this role, you'll need:

• B.A / BSc degree
• 5+ years of professional client facing experience in a B2B client-facing role in the Programmatic / Performance Marketing space - a must
• Ability to provide world-class client service while keeping a focus on growing revenues
• Strong analytical skills - proficient in working with Excel advanced functions. Familiarity with BI platforms such as Tableau / QlikSense / Looker - an advantage
• Love for data-driven decision making - ability to monitor, A/B test and identify trends in data to generate action items and insights
• Excited about complex analytical challenges and enjoy solving them
• Fluency in English
• You are highly motivated, super proactive and dedicated person
• You are a natural collaborator, able to work with multiple teams to reach a common goal
• You are a quick learner with great attention to details and multi-tasking capabilities

Bonus points if you have:

• Experience working with programmatic platforms (SSPs & DSPs) on different types of integrations, preferably OpenRTB
• A love for the challenge of upselling and relationship building with large, international B2B organizations
• Familiarity with different AI tools and the ambition to adopt LLM based functions to improve productivity

How you’ll make an impact:

• Manage a book of business of programmatic partners - understand client strategic objectives & KPIs in order to be able to intelligently identify and execute opportunities, upsell effectively and grow the overall partnership
• Monitor, troubleshoot and optimize performance for different types of client integrations and activities
• Use data analytics tools (Tableau, QlikSense, Excel, etc.) on a daily basis to draw business conclusions and identify opportunities for growth
• Routinely meet & have weekly calls with your clients to share insights & potential initiatives, and review overall performance - backed by data
• Successfully build and maintain close relationships with key people in your book-of-business. Strengthen partnerships with clients and influence their business strategy & decision making
• Develop and execute long-term account plans and conduct QBR (quarterly business review) meetings with strategic clients
• Work very closely with Product Management- as well as other internal teams - to increase client engagement by building new features / improving products based on clients feedback, as well as troubling technical issues

Why Taboola?

If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:

• Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.
• Well-being: Enjoy comprehensive benefits (health, etc.), a fully stocked kitchen, and location-specific perks (gym, parking).
• Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired.
• Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, Expedia and Honda.

Ready to realize your potential?

Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.

Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog.

About Taboola

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.

Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.

#LI-GG1

#LI-Hybrid

Realize your potential by joining the leading performance-driven advertising company!  

Taboola, the world’s largest content recommendation platform, is hiring a Senior Account Manager (Programmatic) for our TLV Office. In this role, you will be directly responsible for managing a book of business of tier-1 clients, identifying and executing upsell & optimization opportunities at scale. 

You will excel in this role if you enjoy working in a highly technological & analytical environment, and love developing rock-solid relationships with international clients.

 To thrive in this role, you'll need:

• B.A / BSc degree
• 5+ years of professional client facing experience in a B2B client-facing role in the online media / performance marketing space
• Ability to provide world-class client service while keeping a focus on growing revenues
• Strong analytical skills - proficient in working with Excel advanced functions. Familiarity with BI platforms such as Tableau / QlikSense / Looker - an advantage
• Love for data-driven decision making - ability to monitor, A/B test and identify trends in data to generate action items and insights
• Excited about complex analytical challenges and enjoy solving them
• Fluency in English
• You are highly motivated, super proactive and dedicated person
• You are a natural collaborator, able to work with multiple teams to reach a common goal
• You are a quick learner with great attention to details and multi-tasking capabilities

Bonus points if you have:

• Experience working with programmatic platforms (SSPs & DSPs) on different types of integrations, preferably OpenRTB
• A love for the challenge of upselling and relationship building with large, international B2B organizations
• Familiarity with different AI tools and the ambition to adopt LLM based functions to improve productivity

How you’ll make an impact:

• Manage a book of business of programmatic partners - understand client strategic objectives & KPIs in order to be able to intelligently identify and execute opportunities, upsell effectively and grow the overall partnership
• Monitor, troubleshoot and optimize performance for different types of client integrations and activities
• Use data analytics tools (Tableau, QlikSense, Excel, etc.) on a daily basis to draw business conclusions and identify opportunities for growth
• Routinely meet & have weekly calls with your clients to share insights & potential initiatives, and review overall performance - backed by data
• Successfully build and maintain close relationships with key people in your book-of-business. Strengthen partnerships with clients and influence their business strategy & decision making
• Develop and execute long-term account plans and conduct QBR (quarterly business review) meetings with strategic clients
• Work very closely with Product Management- as well as other internal teams - to increase client engagement by building new features / improving products based on clients feedback, as well as troubling technical issues

Why Taboola?

If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:

• Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.
• Well-being: Enjoy comprehensive benefits (health, etc.), a fully stocked kitchen, and location-specific perks (gym, parking).
• Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired.
• Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, Expedia and Honda.

Ready to realize your potential?

Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.

Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog.

About Taboola

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.

Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.

#LI-GG1

#LI-Hybrid

Who we are

DV is the leader in digital performance solutions, helping our advertiser and agency partners verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com.

What you will do

You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.

This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.

You will work on core systems that operate at a massive scale, where:

• Data is abundant, but labels are scarce and expensive

• problems are long-tail and ambiguous

• Systems must meet strict latency and cost constraints (pre-bid)

Your responsibilities include:

• Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps

• Design and build models across computer vision, NLP, and multimodal pipelines

• Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment

• Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)

• Improve model quality (precision/recall) while balancing cost, latency, and scale

• Drive automation systems (auto-labeling, auto-curation, retraining loops)

• Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems

• Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward

• Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Who you are

• 3+ years of experience leading Data Science / ML teams

• 6+ years of hands-on experience in Machine Learning / Deep Learning

• Strong background in Computer Vision and/or NLP

• Experience building and deploying production ML systems at scale

• Strong understanding of real-world trade-offs (accuracy, cost, latency)

Technical requirements

• Hands-on experience with deep learning frameworks (PyTorch / TensorFlow)

• Experience with ML/DS tools (scikit-learn, OpenCV, HuggingFace, etc.)

• Experience working with large datasets and model evaluation pipelines

Advantages

• Experience with multimodal systems (vision + text + audio)

• Experience with LLMs / embeddings / foundation models

• Experience with AutoML, active learning, or data-centric AI

#Hybrid#
 

So, what’s the role all about?

How will you make an impact?  

• Lead end‑to‑end research initiatives across NLP, Vision, and multimodal modeling, with a strong focus on LLM‑based and agentic‑AI systems. 

• Architect, prototype, and evaluate singleagent and multiagent systems, including planning, tool use, memory, and orchestration.  

• Establish and own best practices for safe, controllable, and scalable AI agents, including evaluation frameworks, guardrails, fallback strategies, and observability.  

• Act as a technical authority on LLM and agentic systems, guiding architectural decisions, evaluation strategies, and engineering tradeoffs.  

• Define rigorous offline and online evaluation strategies (KPIs, A/B testing, cost/performance tradeoffs) grounded in realworld constraints.  

• Deliver select research components at production quality and partner closely with productization teams to harden and deploy endtoend solutions.  

• Mentor researchers and data scientists, raising the bar for technical rigor, engineering quality, and applied research impact.  

• Communicate complex findings and risks clearly to crossfunctional stakeholders and leadership. 

• Stay at the forefront of AI research, contributing to the team’s agentic‑AI roadmap and long‑term research vision and help set teamwide standards and guidelines.  

Have you got what it takes?

• Skills-first profile with proven, hands‑on impact in applied AI. (Formal degrees welcome but not required.) 

• Strong Demonstrated experience building production‑grade AI agents that perform multi‑step reasoning and tool‑based actions (e.g., tool invocation, planning, memory). 

• Mandatory: Experience with agent frameworks/orchestration layers or custom agent runtimes (e.g., LangGraph/LangChain, semantic routers, workflow engines, or in‑house frameworks). 

• Strong practical expertise with LLMs (AWS Bedrock or similar platforms), including evaluation, prompt/program design, and safety patterns. 

• Strategic problem-solving leadership: You proactively shape ambiguous business questions into well-defined  analytical goals, challenge underlying assumptions, and ensure the work is focused on the problems with the highest impact.  

• Bar‑setting analytical rigor—applied pragmatically: You anticipate bias, confounders, and risks of misinterpretation early, apply the right level of methodological rigor for the decision at hand, and help others distinguish between “theoretically perfect” and “fit for purpose.” 

• Efficient, scalable thinking: You balance depth with speed, favor simple and robust solutions over unnecessary complexity, turn one‑off analyses into reusable insights, and help the organization avoid reinventing or over‑engineering solutions. 

• Track record of translating research into reliable systems in partnership with engineering/product teams. 

• Proficiency in Python and modern ML/DL libraries; strong AI engineering skills (clean architecture, testing, CI/CD, observability), as well as familiarity with HuggingFace or similar model ecosystems and open‑source tooling. 

• Experience applying GenAI to DS workflows (LLM‑as‑a‑judge, synthetic data generation, weak labeling, automated eval). 

• Excellent communication and mentoring skills; fluency in English. 

You will have an advantage if you also have:

• Experience with multi‑agent systems, reinforcement learning, or policy optimization for agent control. 

• Expertise in multimodal or vision‑based deep learning. 

• Operating experience with cloud ML at scale (AWS or equivalent). 

• Leading/mentoring globally distributed teams. 

What’s in it for you?

Join an ever-growing, market-disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

#LI-Hybrid

Requisition ID: 10398

Reporting into: Group Lead, Data Science, CX

Role Type: Individual Contributor

So, what’s the role all about?

How will you make an impact?  

• Lead end‑to‑end research initiatives across NLP, Vision, and multimodal modeling, with a strong focus on LLM‑based and agentic‑AI systems. 

• Architect, prototype, and evaluate singleagent and multiagent systems, including planning, tool use, memory, and orchestration.  

• Establish and own best practices for safe, controllable, and scalable AI agents, including evaluation frameworks, guardrails, fallback strategies, and observability.  

• Act as a technical authority on LLM and agentic systems, guiding architectural decisions, evaluation strategies, and engineering tradeoffs.  

• Define rigorous offline and online evaluation strategies (KPIs, A/B testing, cost/performance tradeoffs) grounded in realworld constraints.  

• Deliver select research components at production quality and partner closely with productization teams to harden and deploy endtoend solutions.  

• Mentor researchers and data scientists, raising the bar for technical rigor, engineering quality, and applied research impact.  

• Communicate complex findings and risks clearly to crossfunctional stakeholders and leadership. 

• Stay at the forefront of AI research, contributing to the team’s agentic‑AI roadmap and long‑term research vision and help set teamwide standards and guidelines.  

Have you got what it takes?

• Skills-first profile with proven, hands‑on impact in applied AI. (Formal degrees welcome but not required.) 

• Strong Demonstrated experience building production‑grade AI agents that perform multi‑step reasoning and tool‑based actions (e.g., tool invocation, planning, memory). 

• Mandatory: Experience with agent frameworks/orchestration layers or custom agent runtimes (e.g., LangGraph/LangChain, semantic routers, workflow engines, or in‑house frameworks). 

• Strong practical expertise with LLMs (AWS Bedrock or similar platforms), including evaluation, prompt/program design, and safety patterns. 

• Strategic problem-solving leadership: You proactively shape ambiguous business questions into well-defined  analytical goals, challenge underlying assumptions, and ensure the work is focused on the problems with the highest impact.  

• Bar‑setting analytical rigor—applied pragmatically: You anticipate bias, confounders, and risks of misinterpretation early, apply the right level of methodological rigor for the decision at hand, and help others distinguish between “theoretically perfect” and “fit for purpose.” 

• Efficient, scalable thinking: You balance depth with speed, favor simple and robust solutions over unnecessary complexity, turn one‑off analyses into reusable insights, and help the organization avoid reinventing or over‑engineering solutions. 

• Track record of translating research into reliable systems in partnership with engineering/product teams. 

• Proficiency in Python and modern ML/DL libraries; strong AI engineering skills (clean architecture, testing, CI/CD, observability), as well as familiarity with HuggingFace or similar model ecosystems and open‑source tooling. 

• Experience applying GenAI to DS workflows (LLM‑as‑a‑judge, synthetic data generation, weak labeling, automated eval). 

• Excellent communication and mentoring skills; fluency in English. 

You will have an advantage if you also have:

• Experience with multi‑agent systems, reinforcement learning, or policy optimization for agent control. 

• Expertise in multimodal or vision‑based deep learning. 

• Operating experience with cloud ML at scale (AWS or equivalent). 

• Leading/mentoring globally distributed teams. 

What’s in it for you?

Join an ever-growing, market-disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

#LI-Hybrid

Requisition ID: 10398

Reporting into: Group Lead, Data Science, CX

Role Type: Individual Contributor

We are looking for a highly skilled Senior Machine Learning Engineer to lead our transition from on-demand, third-party LLM APIs to a fully self-hosted, scalable model ecosystem.

Our core product is an advanced, agentic support chatbot capable of complex reasoning, API tool calling, database lookups, and orchestrating specialized Small Language Models (SLMs) for targeted NLP tasks. As we scale, our current deployment infrastructure (AWS SageMaker) is becoming unsustainable. You will be responsible for architecting, deploying, and optimizing an infrastructure capable of supporting 50 to 100 distinct models ranging from 100M to 70B parameters.

What You’ll Do:

• Inference Optimization: Deploy and manage large-scale models using high-performance inference engines (like vLLM) to ensure low latency and high throughput for our agentic chatbot.
• Agentic Workflows: Develop and refine the chatbot's agentic capabilities, ensuring reliable tool-use, routing, and interactions between massive LLMs and specialized SLMs.
• Model Fine-Tuning: Design and execute fine-tuning strategies to improve model accuracy on specific domain tasks and tool-calling execution.
• Rigorous Evaluation: Build comprehensive offline and online evaluation frameworks to constantly measure model performance and business impact through structured A/B testing.

What We’re Looking For:

Core Engineering & AI Frameworks

• Strong proficiency in Python and Bash scripting.
• Deep experience with PyTorch and the Hugging Face ecosystem.
• Experience using AI coding assistants natively in the terminal, specifically Claude Code, to accelerate development workflows.

LLMs, Inference & Agents

• Proven experience deploying models using vLLM, TGI, or similar high-performance inference servers.
• Strong fundamental understanding of LLM architectures, attention mechanisms, and generation parameters.
• Hands-on experience building Agentic systems (ReAct, function/tool calling, RAG).
• Expertise in fine-tuning strategies (e.g., SFT, RLHF, DPO) and parameter-efficient techniques (PEFT/LoRA).

Statistics & Model Evaluation

• Offline Metrics: Deep understanding of classification/summarization metrics (Precision, Recall, F1, AUC) and retrieval metrics (MRR, NDCG, Precision/Recall @ k).
• Online Metrics & A/B Testing: Strong statistical foundation to design and analyze A/B tests safely, including the use of t-tests, Mann-Whitney U tests, and bootstrapping techniques.

Bonus Points

• Containerization & Orchestration: Experience with Ray for orchestrating large-scale model deployments across multi-GPU clusters.
• Model Quantization: Experience with memory optimization techniques like AWQ, GPTQ, GGUF, or FlashAttention to fit 70B models efficiently onto hardware.
• API Development: Proficiency in building robust, asynchronous microservices using FastAPI to serve model requests.

• Knowledge of Data Engineering principles: dataset collection, cleaning, processing, and scalable storage.

Experience with core MLOps practices, including dataset versioning (e.g., DVC), experiment tracking (e.g., Weights & Biases, MLflow), and model registries.

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Position Overview 

PhaseV is a technology company that redefines clinical development at scale with its enterprise-ready, multi-modal AI/ML platform. With over $65M raised from top investors, we are poised to make a significant impact on how drugs are developed and brought to market - ultimately helping effective treatments reach patients faster. 

We are seeking a talented and driven Applied AI Engineer to join our team. This is a unique opportunity to have a direct and real-world impact using AI by helping redefine how clinical trials are designed, optimized, and run. As an Applied AI Engineer, you will also join a high-caliber, multidisciplinary, cross-functional team spanning engineering, data science, and product. 

This role sits at the intersection of applied AI and product development, with a strong focus on building, deploying, and supporting production-grade AI systems that operate at scale. The ideal candidate will have a strong foundation in NLP and LLMs alongside proven experience building AI-powered services. 

Key Responsibilities 

Technical Development: 

• Build and maintain scalable, production-grade generative AI pipelines that integrate updating unstructured and structured data. 
• Research and develop robust agentic systems to solve complex clinical problems.
• Develop evaluation frameworks for AI systems in clinical contexts. 
• Optimize representation and retrieval strategies to support explainable outputs.
• Contribute to architectural decisions around AI services, APIs, and model orchestration frameworks. 

Research & Analysis: 

• Stay up-to-date with the latest developments in AI, machine learning, and related fields, exploring how emerging technologies can be applied to improve products and services.
•  Document and present methodologies and results for internal and external stakeholders. 

Collaboration: 

• Work cross-functionally with engineering, data science, and product teams. 
• Contribute to technical discussions and peer code reviews. 
• Support the preparation of technical documentation and research papers. 

Qualifications 

Education: 

• Master's in Computer Science, Data Science, Engineering or a related field 
• Ph.D. is an advantage but not required 

Experience: 

• Strong understanding of NLP, LLMs, entity recognition, and evaluation techniques.
• Experience designing and using embedding-based representations, including similarity search and retrieval workflows.
• Hands-on experience building agentic workflows in production environments.
• Proven experience working with unstructured data (e.g., free text, documents, notes) and applying techniques to transform it into structured formats. 
  
  

Skills: 

• Strong programming skills in Python. 
• Ability to clearly communicate complex technical concepts. 
• Experience with data visualization. 
• Strong analytical and problem-solving skills. 
• Ability to work in a dynamic, fast-paced environment. 

Preferred: 

• Experience in the healthcare or biotech industry. 
• Experience with clinical data. 
• Experience with large-scale data processing. 

The Data Science role at Armis is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and Armis family. A data scientist that understands and loves data, and lots of it.

 What you will do...

• Solve Applied Product Challenges: Deep-dive into the Armis product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
• Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
• Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data—such as CVEs, threat intel feeds, and security advisories—to automate the mapping of vulnerabilities to specific business contexts.
• Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
• End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
• Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.

 What we expect...

• Academic Background: M.Sc./PhD in Computer Science, Statistics, Engineering, or a related field (or equivalent high-level professional experience).
• Industry Experience: 6+ years in Data Science, with a heavy focus on NLP and solving complex, real-world problems using ML/Deep Learning.
• Technical Mastery: Hands-on experience with PyTorch, Hugging Face, scikit-learn, and SQL. Familiarity with processing large-scale datasets (PySpark, or similar) is highly valued.
• Domain Awareness: Proven ability to apply statistical modeling to cybersecurity, risk management, or complex system analysis. Experience with Vulnerability Management or Graph Theory is a significant plus.
• Product and collaborative Driven Mindset: You are obsessed with understanding the "Why" behind the data. You enjoy learning the nuances of the product and the cybersecurity domain to ensure your DS solutions are highly applicable.

Curiosity & Grit: A passion for diving into "messy" data and finding the signal within the noise of the modern attack surface.