Senior AI Engineer – Data Science & Generative AI
Mission Build and productionize intelligent AI systems — combining deep data science expertise with engineering rigor to deliver scalable Gen AI solutions.
What You'll Do
- Design and build end-to-end Gen AI and ML pipelines - from data exploration to production deployment
- Develop agentic AI systems: RAG, tool orchestration, planning/execution flows
- Build retrieval services, embedding pipelines, and model-routing infrastructure
- Train, fine-tune, and evaluate LLMs and ML models; implement monitoring and cost-control frameworks
- Translate data science research into robust, production-grade services
- Collaborate with Engineering and Product; contribute to AI architecture decisions
What We're Looking For
- 5+ years in data science, ML engineering, or AI development
- Strong Python with solid software engineering practices
- Hands-on experience with Gen AI: LLMs, prompt engineering, RAG, embeddings, agents
- Deep analytical skills — ability to explore, understand, and interpret complex datasets to select the right approach (statistical, ML, or AI-based)
- Solid grounding in classical data science methods (statistical modeling, feature engineering, hypothesis testing) — knowing when not to use LLMs
- Production deployment of ML/AI systems (APIs, microservices, cloud — AWS/Azure/GCP)
- Familiarity with evaluation frameworks and model observability
Nice to Have
- Vector databases (Pinecone, Weaviate, FAISS)
- LLM fine-tuning or RLHF experience
- Databricks / large-scale data platforms
- Agentic frameworks (LangChain, LlamaIndex, AutoGen)
- Async/streaming architectures
Who You Are Curious and rigorous — you think in experiments but build for production. You bridge the gap between data science and engineering, and care about impact, quality, and reusable foundations.
Skills Required
- 5+ years in data science, ML engineering, or AI development
- Strong Python with solid software engineering practices
- Hands-on experience with generative AI: LLMs, prompt engineering, RAG, embeddings, agents
- Deep analytical skills to explore, understand, and interpret complex datasets
- Solid grounding in classical data science methods (statistical modeling, feature engineering, hypothesis testing)
- Production deployment of ML/AI systems (APIs, microservices, cloud — AWS/Azure/GCP)
- Familiarity with evaluation frameworks and model observability
What We Do
SolarEdge is a global leader in smart energy technology. By leveraging world-class engineering capabilities and with a relentless focus on innovation, SolarEdge creates smart energy solutions that power our lives and drive future progress. Established in 2006, SolarEdge developed the DC optimized inverter solution that changed the way power is harvested and managed in photovoltaic (PV) systems. The SolarEdge intelligent inverter solution maximizes power generation while lowering the cost of energy produced by the PV system, for improved RoI. Continuing to advance smart energy, SolarEdge addresses a broad range of energy market segments through its diversified product offering, including residential, commercial and large scale PV, battery storage and backup solutions, EV charging, home energy management, grid services and virtual power plants, and uninterrupted power supply (UPS) solutions
