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30/07/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for an AI Engineer to join our team. As an AI Engineer , youll be a key member of our founding team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO

Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.
Requirements:
4+ years of professional experience in ML/AI engineering.
Hands-on experience working with LLMs and building AI agents in production environments.
Strong understanding of text classification, ranking, and evaluation in NLP systems.
Proficiency in Python and modern ML frameworks.
Deep knowledge of deploying and maintaining AI systems at scale.
Experience with cloud platforms, particularly AWS.
Experience working independently in fast-paced, mission-driven environments
Bachelors or Masters degree in Computer Science, Data Science, or a related field
This position is open to all candidates.
 
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17/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior AI Engineer to join core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
The Responsibilities:
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.
Requirements:
Must-have:
5+ years of experience in backend or AI engineering with strong coding skills (Python preferred).
Proven experience building and deploying production-grade AI/ML systems.
Strong software engineering fundamentals (data structures, algorithms, system design).
Experience with distributed systems, microservices, and cloud platforms (AWS/GCP/Azure).
Hands-on experience with LLMs and generative AI, including prompt engineering and model integration.
Experience with LLM frameworks and agent orchestration tools (e.g., LangChain, CrewAI, ADK, or similar).
Strong debugging and problem-solving skills, with an ownership mindset.
Nice-to-have:
Experience with ML frameworks such as PyTorch or TensorFlow.
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD for ML).
Background in NLP, LLM optimization, or agent-based systems in production.
Experience with large-scale data pipelines and NoSQL databases.
Experience with model evaluation, monitoring, and continuous improvement in production environments.
Contributions to open-source projects or research publications.
This position is open to all candidates.
 
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30/07/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Senior Data Scientist to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. Youll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions.

This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform.



What Youll Do:

Own End-to-End Model Development (Research → Production)

Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization.

Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks.

Ensure models are robust, explainable, and production-ready in real-world enterprise environments.

Partner Deeply with Product & Engineering

Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives.

Work hands-on with engineering to integrate models into production systems and data pipelines.

Balance research depth with pragmatic execution and business impact.

Build AI Security Intelligence

Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability.

Work with structured and unstructured data, including logs, prompts, model outputs, and metadata.

Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors.

Lead Research POCs & Innovation

Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product.
Requirements:
5+ years of experience in Data Science or Applied ML roles.

3+ years of backend development experience, working with production systems.

Strong hands-on experience with language models / LLMs and modern ML techniques.

Bachelors degree in Computer Science (or equivalent practical experience).

Proven experience owning end-to-end research POCs, from ideation to real-world impact.

Strong understanding of product and business value, with a bias toward lean, effective solutions.

Deep understanding of language models
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Data Science & ML-Ops Team Lead to lead a multidisciplinary team of Data Scientists and ML Engineers responsible for designing, building, deploying, and operating production-grade machine learning systems.
This is a highly technical leadership role that combines applied machine learning understanding, software engineering, distributed systems, and MLOps. You will own the end-to-end lifecycle of our AI capabilities - from data and feature engineering to model training, deployment, monitoring, experimentation, and continuous improvement.
You will play a key role in defining the architecture, engineering standards, and operational practices behind fraud detection systems that protect millions of users globally in real time.
If you are passionate about building intelligent systems at scale and transforming machine learning into reliable production services, we want to meet you.
What youll do:
Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.
Requirements:
Lead, mentor, and grow a team of Data Scientists and Engineers, fostering a culture of technical excellence, ownership, and innovation.
Drive the strategy, architecture, and roadmap for Machine-Learning and AI-powered Detection & Response capabilities.
Design, train, evaluate, and optimize machine learning models for fraud prevention, risk assessment, and anomaly detection.
Own the end-to-end ML lifecycle, including feature engineering, experimentation, deployment, strict monitoring, and continuous improvement.
Build and scale ML platforms, tooling, and MLOps practices to enable reliable, efficient, and reproducible model development and operations.
Build low-latency, production-grade inference services and scalable distributed systems.
Collaborate closely with Product, Engineering, Security, and Customer teams to deliver impactful AI solutions and measurable business outcomes.
Advantages:
Experience with fraud detection, identity security, cybersecurity, risk engines, or behavioral analytics.
Experience designing low-latency inference architectures and real-time decisioning systems.
Experience building ML platforms and internal AI tooling.
Experience with Kubernetes, Docker, Kafka, Spark, Airflow, Flink, or similar distributed systems technologies.
Experience with feature stores, vector databases, model registries, and modern MLOps platforms.
Experience with AWS, GCP, or Azure.
Familiarity with LLMs, GenAI applications, AI evaluation frameworks, and agentic systems.
Background in Data Engineering, Platform Engineering, or Backend Engineering.
Experience operating mission-critical systems with strict latency and availability requirements.
B.Sc. or higher degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.
Requirements:
3+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
Strong proficiency in Python
Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
Fluent with AI-powered development tools like Cursor and Claude Code, and genuinely curious about what's next in GenAI, LLMs, and AI agents
Familiarity with AI concepts like RAG, embeddings, mixture-of-experts, prompt crafting, and LLM context engineering - an advantage
Sharp problem-solving instincts and the ability to move fast without cutting corners
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
Ready to work in an office environment most days of the week.
This position is open to all candidates.
 
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17/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.
Requirements:
What You Bring
5+ years of hands-on work in machine learning / deep learning, including 3+ years focused on NLP / language models.
Proven track record of training and fine-tuning transformer-based models (BERT-style, encoder-decoder, or LLMs), not just consuming hosted APIs.
Strong programming skills in Python and at least one major deep learning framework (PyTorch preferred; TensorFlow).
Solid understanding of transformer architectures, attention mechanisms, tokenization, positional encodings, and modern training techniques.
Experience building data pipelines and tools for large-scale text / log / code processing (e.g. Spark, Beam, Dask, or equivalent frameworks).
Practical experience with ML infrastructure, such as experiment tracking (Weights & Biases, MLflow or similar), job orchestration (Airflow, Argo, Kubeflow, SageMaker, etc.), and distributed training on multi-GPU systems.
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.
Ability to own research and engineering projects end-to-end: from idea, through prototype and controlled experiments, to models ready for integration by product and platform teams.
Good communication skills and the ability to work closely with non-ML stakeholders (security experts, product managers, engineers).
This position is open to all candidates.
 
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03/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As an AI Research Team Lead on Research group, you will mentor a talented team of researchers, set the strategic vision for research initiatives, and drive team-wide project goals. Youll partner closely with Product and Engineering leadership to turn open-ended data-security challenges into measurable experiments and shipped features. You will manage the critical balance between research exploration and product delivery, owning the end-to-end lifecycle-from problem framing and data strategy to evaluation, deployment, and ongoing monitoring-helping customers discover, protect, and govern their data at scale.



What Youll Do

Lead and mentor a team of AI researchers, fostering a culture of excellence and innovation while overseeing the end-to-end research lifecycle.
You will act as the technical and strategic lead, defining team priorities, roadmap, and data science methodologies.
Mentor and grow team members through technical guidance, career development, and peer reviews.
Collaborate with cross-functional leadership in Product and Engineering to align research efforts with core business objectives and customer needs.
Manage team performance, resource allocation, and timely project delivery within an agile environment.
Develop, evaluate, and maintain deep learning and NLP solutions to enhance Cyeras core capabilities in sensitive data classification.
Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems
Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification.
Join a full stack AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise.
Requirements:
BSc in computer science, math, physics, or a related field
7+ years of experience as an AI Researcher/NLP Researcher/Applied Scientist, including experience leading or managing research teams
Proven track record of building and managing high-performing AI research / Data Science teams.
Solid grounding in core machine and deep learning concepts and techniques, data challenges (imbalance, scaling etc.), and evaluation.
Demonstrated expertise in applying LLMs - prompt engineering and prompt tuning (few-shot, chain-of-thought, tool/function calling, routing), task adaptation (instruction/SFT, PEFT/LoRA, DPO/RLHF), retrieval-augmented generation, rigorous evaluation and production deployment with appropriate safety, latency, and cost controls.
Self-learner, initiator, able to quickly learn new technologies
Experience in NLP - a significant advantage
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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03/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As an AI Researcher on Research group, youll research, develop and productionize LLMs powered applications and AI-agents. Youll partner closely with Product and Engineering to turn open-ended data-security challenges into measurable experiments and shipped features. Youll own the end-to-end lifecycle - from problem framing and data strategy to evaluation, deployment, and ongoing monitoring - helping customers discover, protect, and govern their data at scale.



What Youll Do

Responsible for the end-to-end research process. This includes identifying problems, preparing data, tuning and developing models, deploying to production, and analyzing outcomes.
You will be a hands-on domain leader, laying the foundations of our data science workflows and algorithms. This is an excellent opportunity to work with endless amounts of data and creatively generate insights that will increase the ability to classify tons of data.
Develop, evaluate, and maintain deep learning and NLP solutions to enhance core capabilities in sensitive data classification.
Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems
Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification.
Join a full stack AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise.
Requirements:
MSc in Computer Science, Mathematics, Statistics, Physics or a related field
5+ years of experience as a Data Scientist/AI Researcher/NLP Researcher/Applied Scientist
Strong knowledge and understanding of machine learning concepts and techniques.
Deep understanding in modern NLP: LLMs, transformers, etc.
Proven experience in applying LLM-based applications or AI agents.
Experience in deploying and optimizing ML / LLMs / AI-agents to production processes
Experience with data pipelines / big-data analytics
Self-learner, initiator, able to quickly learn new technologies
This position is open to all candidates.
 
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09/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a hands-on AI Engineer to build and own the agentic workflows at the heart of our security intelligence engine.
This is a backend-focused engineering role: youll design, build, and maintain the autonomous systems that execute security workflows end-to-end - taking capabilities from research prototype to scalable, production-grade infrastructure.
Youll be working at the edge of applied AI, turning LLMs and agentic frameworks into reliable, observable systems that operate in real customer environments.
What Youll Build:
Agentic Workflows (Core Focus): Design and maintain the orchestration backbone for multi-step, autonomous agents that investigate, reason about, and act on complex security operations.
Internal AI Infrastructure: Contribute to a shared platform for models, data pipelines, training, evaluation, and observability that the whole AI team builds on.
Responsibilities:
Build and maintain the agentic workflow engine - orchestration, tool use, state management, retries, and evaluation - that powers our AI-driven security features.
Develop the backend services and APIs that deploy AI capabilities safely and at scale.
Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
Own reliability, observability, and performance of the agentic systems in production.
Requirements:
Mid-to-senior engineering experience, or relevant technical military experience.
Strong backend engineering background with a focus on ML/AI systems.
Hands-on experience building with **LLMs and agentic frameworks** in production.
Comfort operating in a fast-paced environment, bridging research and product engineering.
Strong Advantages:
Experience with LangChain / LangGraph (or comparable agent-orchestration frameworks) - a significant plus for this role
Experience with evaluation frameworks and observability for non-deterministic AI systems.
This position is open to all candidates.
 
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19/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are a fast-paced, technology-driven team where everyone's contribution impacts product success.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.

This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.

The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.

Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.

What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.

Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.

This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help our company move faster, automate smarter, and turn ideas into measurable business wins.

What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.
דרישות:
2-5 years of hands-on experience in AI Engineering, Data Engineering, Software Engineering, Data Science, Analytics Engineering, or a similar technical role.
Proven experience building and deploying AI-powered products, workflows, agents, automations, or business solutions in a real company environment.
Strong hands-on experience with LLMs, AI agents, prompt engineering, RAG, workflow automation, APIs, or AI development frameworks.
Ability to code and build practical solutions using Python, SQL, JavaScript/TypeScript, or similar languages.
Strong data experience, including ETLs, data pipelines, APIs, databases, data warehouses, and Snowflake.
Experience working in a SaaS or B2B technology company.
Strong business acumen, ownership, and communication skills, with the ability to work independently with stakeholders and drive projects from idea to production.
Degree in Engineering, Computer Science, Mathematics, Statistics, Physics, or a related quantitative field - advantage
Advantages
Experience with agent frameworks, RAG systems, vector databases, orchestration tools, Snowflake, Airflow, Rivery, Gitlab, Claude, OpenAI, or similar tools.
Experience working in a cybersecurity or data company.#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a talented and motivated Data Scientist for a temporary position to support our growing data, analytics, and AI automation needs. This role focuses on turning large volumes of data into models, insights, and intelligent automation - combining classic data science (statistical analysis, feature engineering, machine learning) with the emerging Agentic AI stack (LLMs, MCP, agent orchestration). You will work closely with data engineers and internal teams to prototype and productionise models, build LLM-powered agents and workflows, and support the integration of AI capabilities across the organization.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.


Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.
Requirements:
Knowledge and Experience
3+ years of experience as a Data Scientist, ML Engineer, or in a similar analytical role.
Strong programming skills in Python, with experience writing reusable libraries and working with data manipulation and ML libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow).
Solid grounding in statistics and machine learning: feature engineering, model selection, validation, and interpreting results for a business audience.
Hands-on experience with LLMs and Agentic AI: prompt engineering, retrieval-augmented generation (RAG), tool/function calling, and building or consuming agent frameworks.
Advanced proficiency in SQL and experience working with large-scale databases (e.g., PostgreSQL, MSSQL, Oracle).
Experience with AI/ML workflows, supporting model training, inference, and evaluation pipelines in production environments.
Genuine curiosity and a strong appetite to learn - eager to bring existing knowledge to the team and to grow it further.

Preferred Knowledge and Experience
Background in finance, trading systems, or financial market data.
Experience building or consuming MCP (Model Context Protocol) servers and clients.
Experience with workflow automation / orchestration platforms such as n8n, Airflow, or similar.
Experience with data visualisation and BI tooling for communicating analytical results.
Exposure to real-time data processing technologies (e.g., Kafka, Spark Streaming).
This position is open to all candidates.
 
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