דרושים » תוכנה » Algorithm Developer

We are now hiring our first Prompt Engineer to join the Product team and lead the development of GenAI-powered experiences. Youll work across multiple product lines to design and implement production-grade prompt architectures, embed AI agents into the user journey, and scale experimentation with cutting-edge LLM tools.

Product Team Member Prompt Engineer

This role blends hands-on AI development with product integration strategy. Youll collaborate with product managers and engineers to design, evaluate, and iterate on generative AI solutions including multi-step prompt chains, agent workflows, and LLM selection frameworks. Your work will shape how personalization evolves across the Dynamic Yield platform.

All About the Role

Design and refine prompt architectures (e.g., few-shot, chain-of-thought, tool use) that drive our LLM-powered features

Select and evaluate models, frameworks, and orchestration tools (e.g., OpenAI, Claude, LangChain, RAG)

Collaborate with engineers to implement scalable agent-based workflows and integrate GenAI into the product

Partner with Product Managers to define user-facing use cases and influence product direction with AI capabilities

Develop internal tooling and evaluation frameworks to test prompt quality, model behavior, and UX alignment

Act as a thought leader on prompt best practices, model safety, and responsible AI design across product squads

Required Senior Deep Learning Algorithm Developer
We are a global leader in autonomous vehicle (AV) technology. If youre an experienced deep learning developer driven by a passion to shape the future of mobility, join us to make AV a reality.
Object Perception team leverages cutting-edge multi-task deep learning to provide AVs with a rich understanding of vehicle behavior and interactions. Using vast amounts of video data, our algorithms capture intricate semantics and time-sensitive features, forming the backbone of AV scene understanding.
What will your job look like?
Design, develop, and optimize deep learning models that extract complex, dynamic insights from real-world scenes.
Collaborate across teams to solve key technical challenges and ensure model scalability.
Research and integrate the latest advancements in multi-task learning, temporal analysis, and AI architectures into our solutions.
Enhance and refine algorithmic performance through rigorous experimentation and innovation.
Develop primarily in Python, with occasional work in C++.
Work environment: Hybrid schedule: 4 days in-office (Tel Aviv or Jerusalem) and 1 day remote.

Required Senior Deep Learning Algorithm Developer- L2++ Group
Description
A leading AI Company in the Automotive Industry, is expanding! Following recent major design wins with leading global OEMs, we're scaling up our operations and innovation efforts. This is your chance to be part of a groundbreaking company at the forefront of automotive safety and intelligence.
We are looking for passionate individuals who want to make a real impact, working on state-of-the-art AI solutions that save lives and transform the driving experience. Join us in shaping the next generation of automotive technology.
Responsibilities
As part of the algorithm team for the next generation of autonomous driving, you will:
Understand deeply, implement, train, and evaluate recent state-of-the-art algorithms in computer vision (e.g. object detection, semantic segmentation, self-supervised learning, vision transformers) for various domains, including ground-view images and satellite/aerial images.
Adapt algorithms into robust and scalable production-ready algorithms. Write clean and efficient code, ensuring compatibility with existing systems and frameworks and real-time needs. Take full responsibility for your algorithms end-to-end until deployment on the edge device for production.
Develop and implement new computer vision algorithms (architectures, loss functions, post processing, training and evaluation methods) that surpass SOTA algorithms and achieve desired performance levels in our domain.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

As an AI Data Science Team Lead, you will lead the Clinical AI domain in the Data & AI group. You will be responsible for building, deploying, and evolving clinical prediction models and LLM based agents that power our AI-first user experiences - starting with our conversational health assistant and expanding into risk prediction and disease management.
You will lead a cross functional team of data professionals and work closely with Product, R&D, and Data Platform teams to bring data-driven ML/AI solutions to life.
Responsibilities:
Lead a team of data scientists & analysts
Work closely with the engineering team on delivering AI agents to our product - collaborate on design, testing, deployment, monitoring and iterative improvements
Establish best practices for agent observability & evaluation
Partner with Product Managers to translate user journeys into intelligent conversational flows
Define how real-time data from the app, wearables & clinical events is injected into agent memory
Implement other novel algorithms and investigate new technologies to improve the clinical impact of our product and actually save lives!!

We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software.
Location: Haifa \ Tel-Aviv in hybrid model.
Responsibilities
Develop advanced ML algorithms using data from our Agents embedded in silicon. Example domains include:
Lifetime predictions
Clustering and dimensionality reduction
Parametric modeling and screening
Time-series forecasting
Lead end-to-end algorithm lifecycle: ideation → research → POC → design → implementation → validation → deployment.
Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions.
Drive integration of AI-enhanced tools and intelligent pipelines into ML workflows.

Were looking for an experienced MLOps / DevOps Engineer to design and manage the infrastructure powering large-scale machine learning systems. Youll be responsible for deploying GPU-heavy models (including LLMs) on cost-efficient, production-grade infrastructure, supporting both ML workflows and application artifact delivery.

Youll work with cutting-edge technologies like vLLM, Triton, SageMaker, ClearML, Karpenter, KEDA, and EKS, ensuring the right balance between performance, scalability, and cost.



What Youll Do

Deploy and manage LLMs and deep learning models using vLLM, Triton Inference Server, and custom API endpoints.

Build and maintain GPU-aware autoscaling clusters using AWS EKS, Karpenter, and KEDA, optimizing for cost-efficiency and performance.

Develop CI/CD pipelines using Jenkins and GitHub Actions to automate ML model delivery and application deployments.

Orchestrate training, fine-tuning, and inference jobs on AWS SageMaker and ClearML, with support for experiment tracking, versioning, and reproducibility.

Support backend teams in deploying app artifacts and runtime environments; implement rollback and release strategies.

Integrate observability tooling (e.g., Prometheus, Grafana, ELK, or OpenTelemetry) for both infrastructure and model performance.

Collaborate with SREs to enforce high availability, disaster recovery, and incident response procedures for mission-critical AI services.