We are on the search for a Senior Machine Learning Engineer who will join our Data team in Tel Aviv. As a Senior ML Engineer in a Data-Driven company, you will have a significant opportunity for impact. You will be part of the team that turns data into solutions that influence the product and drive strategic business decisions that shape the direction of the company.
Here are a few of the things you will do:
Own the end‑to‑end ML lifecycle: design, build, and operate data ingestion, feature‑store, training, evaluation, CI/CD, and low‑latency serving pipelines that power AI experienceslead qualification, generative content, conversational assistance, and more.
Collaborate deeply with AI researchers, engineering managers, and product managers to transform product ideas into reliable, scalable ML systems, iterating quickly from prototype to production.
Advance our MLOps platform by developing orchestrations, model registries, automated monitoring, and retraining workflows that enable shipment of AI features autonomously and safely.
Elevate engineering culture through code reviews, documentation, mentorship, and promoting experimentation and data‑driven decision making.
Here are a few of the things you will do:
Own the end‑to‑end ML lifecycle: design, build, and operate data ingestion, feature‑store, training, evaluation, CI/CD, and low‑latency serving pipelines that power AI experienceslead qualification, generative content, conversational assistance, and more.
Collaborate deeply with AI researchers, engineering managers, and product managers to transform product ideas into reliable, scalable ML systems, iterating quickly from prototype to production.
Advance our MLOps platform by developing orchestrations, model registries, automated monitoring, and retraining workflows that enable shipment of AI features autonomously and safely.
Elevate engineering culture through code reviews, documentation, mentorship, and promoting experimentation and data‑driven decision making.
Requirements:
5+ years building data‑intensive or distributed production systems with Python and relevant ML ecosystems, shipping production software.
3+ years deploying machine‑learning models (classical and/or LLM) in cloud environments (AWS/GCP/Azure) with containers and Kubernetes.
Hands‑on experience with MLOps toolstooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Feast or equivalent).
Proven track record creating robust data/feature pipelines for ML and instrumenting real‑time monitoring for drift and performance.
Strong software‑engineering fundamentals: version control, automated testing, CI/CD, security, and cost awareness.
Excellent collaboration and communication skills in Hebrew and English; comfortable working closely with cross‑functional partners and mentoring peers.
Mindset of ownership, curiosity, and bias for action in a fast‑moving environment.
5+ years building data‑intensive or distributed production systems with Python and relevant ML ecosystems, shipping production software.
3+ years deploying machine‑learning models (classical and/or LLM) in cloud environments (AWS/GCP/Azure) with containers and Kubernetes.
Hands‑on experience with MLOps toolstooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Feast or equivalent).
Proven track record creating robust data/feature pipelines for ML and instrumenting real‑time monitoring for drift and performance.
Strong software‑engineering fundamentals: version control, automated testing, CI/CD, security, and cost awareness.
Excellent collaboration and communication skills in Hebrew and English; comfortable working closely with cross‑functional partners and mentoring peers.
Mindset of ownership, curiosity, and bias for action in a fast‑moving environment.
This position is open to all candidates.
