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As a Staff Software Engineer, you will serve as a technical authority and play a pivotal role in scaling our core platform. Your focus will span architecture, security research, and engineering excellence:

Lead & Architect: Design, build, and scale high-performance software while driving architectural best practices across the R&D organization.
Security & AI Innovation: Drive deep-dive research into cloud, SaaS ecosystems, and AI agents to build proactive detection models, mitigation strategies, and threat intelligence.
Engineering Excellence: Elevate code quality, testing standards, system monitoring, and documentation across teams.
Cross-Functional Ownership: Partner closely with Product and R&D to translate complex security requirements into scalable technical solutions.
Scale & Optimize: Identify and resolve systemic performance bottlenecks and architectural challenges.
Mentorship & Leadership: Act as a technical mentor, driving engineering standards and fostering a strong knowledge-sharing culture.

Role Overview: You will take ownership of the search infrastructure for Ask Seeking Alpha - a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, news) in milliseconds. You will work on the Retrieval layer of our RAG architecture, combining traditional text search with modern vector search techniques.

Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.

What You'll Do
Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.
This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.
This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

Required Senior Data Engineer
About the role:
You will specialize in designing and building world class, scalable data architectures, ensuring reliable data flow and integration for groundbreaking biotechnological research. Your expertise in big data tools and pipelines will accelerate our ability to derive actionable insights from complex datasets, driving innovations in improving patients outcome and in delivering life savings treatment solutions.
In this role, you will work closely with data scientists, AI/ML engineers, architect and other cross-functional teams to understand their data needs and requirements. You will also be responsible for ensuring that data is easily accessible and can be used to support data-driven decision making.
Location: Ramat Gan, (Hybrid model)
What will you do?
Design, build, and maintain data pipelines that ingest, transform, and load noisy, heterogeneous biological data at scale - from single-cell sequencing, genomic, and clinical sources - across databases, APIs, and flat files
Enhance our data warehouse system to dynamically support multiple analytics use cases
Implement and productize complex scientific and computational algorithms as scalable, production-grade pipeline components
Drive our data infrastructure toward becoming AI-native, enabling AI/ML systems and agents to reliably query, reason over, and act on our data
Implement data governance policies and procedures to ensure data quality, security, and privacy
Collaborate with ML and AI scientists and other cross-functional teams to understand their data needs and requirements
Drive team capability growth by championing an AI-first SDLC, mentoring data engineers on AI-assisted development practices and tooling
Develop and maintain documentation for data pipelines, processes, and systems
Requirements
We will only consider senior data engineers that have demonstrated strong system design skills combined with an extensive background working with data orchestration, data warehousing and ETL tools.

We are looking for a Senior AI Researcher to join our foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.
In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.
You do not need prior biology experience - but you should be excited to apply your deep learning expertise to a new scientific domain.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
Tackle challenging modeling problems with thoughtful, principled approaches.
Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.

We are a fast-moving startup developing breakthrough digital printing technology for optical lens coatings. We are seeking a highly motivated and experienced Director of Automation to lead our multidisciplinary Automation group. This key leadership role holds disciplinary responsibility over the mechanics, software, control, and electrical engineering teams. The ideal candidate will thrive in a dynamic startup environment, driving the team forward with a strong sense of ownership, excellent interpersonal skills, and a collaborative mindset. You will oversee the development of cutting-edge technologies, manage the delivery of the software and control systems, and ensure successful technological implementations at customer sites.


Key Responsibilities:

Multidisciplinary Leadership: Provide direct management and disciplinary leadership for the mechanics, software, control, and electrical engineering teams.
Delivery Management: Lead and manage complex software and control plans from concept through development to successful deployment.
Technology Development & Innovation: Drive the research, design, and development of new automation technologies to enhance our industrial equipment platforms.
Customer Implementation & Support: Oversee the deployment and integration of new technologies, ensuring seamless implementation at customer site and providing ongoing top-tier support.
Teamwork & Collaboration: Foster a culture of exceptional teamwork and cross-functional collaboration. Work closely with other R&D groups: System Engineering, Process, Materials, Integration & Testing as well as with Operations and Customer support.
Execution & Ownership: Take full ownership of the Automation roadmap. Push projects forward proactively, overcome obstacles in a fast-paced environment, and lead the team to meet ambitious technological and business milestones.

Required Customer-Facing Data Scientist - Demand Forecasting
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

Required Senior ML Engineer
Responsibilities:
Work on our core data and machine learning infrastructure, which is at the heart of our offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.
Who You Are:
A problem solver at heart, you have a passion for excellence, you love to learn but know when its time to deliver and make ends meet. You arent threatened by a complex, dynamic and demanding environment. There is no I in team, is a motto you believe in deeply and you are always looking out for your peers. You know how to take ownership and drive projects to completion.