לוח משרות דרושים NLP/Machine Learning

We are seeking an AI/ML Lead Engineer to join our R&D division and drive the adoption of advanced machine learning and AI solutions across our financial and operational domains. In this role, you will design and implement intelligent models that increase efficiency in collections and payments processing and build AI-driven tools that enhance call center performance and agent productivity.
We are looking for a hands-on, independent team player with strong foundations in data science, computer science, and backend engineering, combined with excellent analytical and algorithmic skills. This role is diverse and impactful, spanning machine learning development, data analysis, and backend engineering, with the opportunity to shape our AI/ML strategy for servicing and operations.
As part of the R&D group, you will work closely with engineers and product managers, leading and implementing AI/ML initiatives that directly align with our business goals and innovation vision.
Key Responsibilities
Lead the design, development, and deployment of ML models to optimize collections and payments processing.
Develop and integrate AI-driven tools to improve call center efficiency and agent productivity.
Collaborate cross-functionally with engineers, product managers, and stakeholders to translate business needs into technical solutions.
Drive data analysis and modeling efforts, leveraging advanced algorithms to uncover insights and improve decision-making.
Ensure scalability, quality, and compliance of all AI/ML solutions within the financial and servicing domains.
Stay up to date with emerging AI/ML technologies and assess their potential impact on the companys strategy.
Mentor and guide team members, fostering knowledge-sharing and technical excellence.

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of our primary product. This involves working on core systems, such as POS underwriting models, models for merchant operations, and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities:
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g., using SHAP values for model explainability and providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at our company. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of our companys risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing our companys financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for our company's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and our company practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at our company
Identify and Initiate New Business Opportunities: - Collaborate with our company FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst at our company look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of our companys data and algorithms.
Utilize your deep understanding of our companys data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

When leading companies choose our company Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use our company Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales our companys by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to our company Cloud products.
As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate our company Cloud to our customers. You will help prospective and existing customers and partners understand the power of our company Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on our company Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply the impact of the team as a whole.

our Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our companys cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to our company Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to our company Cloud.
Work directly with our company Cloud products to demonstrate and prototype integrations in customer and partner environments.

We are seeking a talented Image Processing Engineer to join our team. The job will focus on developing deep learning solutions for image restoration in new imaging systems. You will be part of an interdisciplinary team driving products.
Description:
Deep learning development:
Design, implement, and optimize deep learning models for various tasks in the field of Image restoration. Implement and validate models using various data sets.
Prepare, filter, process, and analyze large-scale datasets to train and evaluate models.
Analyze the results of your algorithm and compare with other leading methods.
Optimize models for real-time performance and resource efficiency.
Research:
Explore how algorithm approaches can mitigate artifacts of new imaging systems.
Investigate sensor fusion techniques for these applications.
Stay updated with recent advancements in the field.
Collaboration:
Work in sync with interdisciplinary teams of SW, HW and Camera Architecture engineers.
Integrate models into larger products or research studies.