Senior ML & LLM Platform Engineer
Jones Lang LaSalle Incorporated1 day ago
Tel Aviv-Yafo, IsraelSenior
Responsibilities
- Serve open-weight LLMs at scale by managing GPU capacity, autoscaling, throughput, batching, quantization, caching, tool use, and cost per token.
- Set MLOps and LLMOps standards for experiment tracking, model and prompt registries, infrastructure-as-code, release practices, monitoring, and evaluation.
- Build evaluation, regression, observability, and cost-tracking systems for non-deterministic LLM pipelines.
- Create development and pre-production platforms where large-scale experiments are fast, reproducible, tracked, and safe to run against real data.
- Improve the CI/CD, engineering, and cloud foundations supporting ML and LLM pipelines for performance, cost, reliability, and data-scale operation.
- Design and productionize agentic AI services and applications, including multi-agent systems, visual interfaces, RAG solutions, and other GenAI technologies.
- Work closely with data scientists and researchers on ML, GenAI, distributed training, and inference systems.
Requirements
- At least 5 years of experience in MLOps, ML, AI, data engineering, or software engineering.
- Production experience deploying and operating systems at scale and a proven track record working with data scientists and researchers.
- Hands-on experience with LLMs, vector databases, RAG, MCP, agent platforms, open-weight models, orchestration, architecture, caching, monitoring, latency, throughput, and cost management.
- Fluency with MLOps and LLMOps tooling, including experiment tracking, model and prompt registries, and production monitoring such as MLflow or equivalent tools.
- Deep understanding of LLM architectures and techniques including Mixture-of-Experts, attention variants, tokenization, quantization, KV caching, and batching.
- Practical experience with distributed training and inference parallelism, including FSDP, data parallelism, tensor parallelism, and pipeline parallelism, is advantageous.
- Bachelor of Science degree in computer science, mathematics, or another quantitative field, or equivalent experience; a master’s degree is advantageous.
- Generalist capability across operations, data engineering, agent development, and data science.
- Experience with cloud and DevOps foundations, AWS, Azure, or GCP; Databricks or Snowflake; Spark; infrastructure-as-code; CI/CD; and scheduled data pipelines is advantageous.
- Experience in data science, applied research, or building agentic systems is advantageous.
- Entrepreneurial mindset and interest in emerging technologies, state-of-the-art systems, and organizational enablement.
Benefits
- Hybrid work arrangement from JLL’s renovated Tel Aviv headquarters, with the listed location marked on-site in Tel Aviv, Israel.
- Private health insurance.
- Team breakfasts and an on-site gym.
- Competitive compensation and benefits; compensation figures are not stated.
Tech Stack
Categories
About Jones Lang LaSalle Incorporated
JLL is a global commercial real estate services and investment management firm serving occupiers and investors. It provides property and facilities management, leasing and tenant representation, capital markets, project and development services, workplace strategy, sustainability, and real estate technology and analytics, with a fee- and commission-based advisory, outsourcing, transaction, and management-fee model. Headquartered in Chicago, it is a public company listed on the NYSE (JLL).