לוח משרות דרושים NLP/Machine Learning בנתניה

Were seeking a Senior/Lead Generative AI Developer to join our Core GenAI Team. This role is ideal for someone passionate about building AI-powered features, improving platform foundations, and experimenting with cutting-edge research and prototypes. Youll work across product-facing initiatives as well as internal tools, helping shape how Generative AI is leveraged.

You will take a hands-on role in coding and system design while also mentoring other developers and guiding best practices for AI development. This position combines deep technical work with cross-functional collaboration to push the boundaries of how GenAI can improve both platform and the public transportation industry.

Responsibilities

Building & Evolving GenAI Capabilities
Design, develop, and maintain backend infrastructure for AI-powered features (APIs, orchestration, LangChain/RAG pipelines, Agents orchestration and flow design, integrations with LLMs).
Collaborate with Product and Design to deliver AI-driven experiences in the Optibus platform, focusing on intuitive and impactful user interactions.
Explore and prototype new applications of Generative AI that can enhance public transportation planning, scheduling, and operations.
Ensuring Technical Excellence
Establish and promote best practices for AI development, evaluation, and monitoring in production environments.
Mentor and guide developers on the RnD and Product teams in adopting GenAI tools and patterns.
Drive experiments with emerging models, frameworks, and techniques to ensure the platform remains state-of-the-art.
Cross-functional Collaboration

Own and drive GenAI integrations into products, ensuring scalability, reliability, and performance.
Partner with Product Managers, Designers, and other engineering groups to align on requirements and technical feasibility.
Act as a thought partner across teams, identifying synergies and preventing redundant work.

We are looking for a Senior Technical Product Manager to lead products and initiatives that require deep technical expertisespanning APIs, integrations, data platforms, and next-generation GenAI-powered services. This role combines customer-facing product ownership with strong technical skills to define and deliver solutions that power mission-critical workflows for global transit agencies and operators.

Responsibilities

Product Ownership Lead the end-to-end lifecycle of technical product areas, including integration frameworks, APIs, data pipelines, and AI-driven services.
GenAI Leadership Define and drive the roadmap for GenAI-powered features across the platform, from intelligent assistants and automation workflows to AI-driven analytics and optimization.
Technical Depth Collaborate with engineering to design scalable architectures, define data models, and evaluate trade-offs between performance, usability, and maintainability.
Customer & Market Discovery Engage with enterprise customers, partners, and internal stakeholders to understand technical requirements and translate them into product capabilities.
Cross-Functional Leadership Partner with engineering, design, solutions engineering, and go-to-market teams to ensure successful launches and adoption.
Platform Vision Contribute to Optibus platform strategy by defining standards for interoperability, modularity, and extensibility (e.g., APIs, SDKs, integrations, GenAI orchestration).
Execution Excellence Write detailed product specs, acceptance criteria, and success metrics; manage the backlog and prioritize effectively in fast-moving contexts.
Thought Leadership Represent Optibus in technical and industry forums, positioning our platform as the backbone of modern transportation operations and a leader in applied GenAI.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our Machine Learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, Machine Learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. Support reproducibility and consistency across model training environments. Implement and manage Artifactory. Establish and maintain model registries to track versions, metadata, and lineage. Automate model promotion through staging, testing, and production environments. Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments Optimize GPU/CPU resource utilization and cost efficiency. Implement auto-scaling and load balancing strategies for ML workloads. Manage version control systems (e.g., Git) and integrate with experiment tracking tools. Handle Storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.