As our AI Applied Researcher, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore, research, and develop cutting-edge solutions that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team, you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the technologies in the world, witnessing firsthand their impact on our customers.
A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Research, design, and build anomaly classification, predictive, insights, recommendations, and other types of models from various data sources, including sensor time-series data, textual data, images, and more.
You will Ensemble multi-modalities by exploiting and enriching the most from our data collections platform and feature extraction and store phases, using classic statistical methods, deep learning, Transformers, Graphs, Foundations Modules (as TSFM, Graph Transformer, TGNN), and any available technology to extract recommendations for taking real-world, life-changing actions.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Work with cloud-based big data platforms for training, distributed processing & experiments tracking (e.g., Metaflow, Grafana, Outerbounds, Databricks).
Partnering and contributing to modern technologies: LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.
As part of our hybrid working policy, you will be expected to work from the office at least twice weekly, which includes at least one day in Haifa.
Requirements: M.Sc., or Ph.D. in Electrical Engineering, Computer Science, Physics, Mathematics, or a related field.
4+ years of experience in ML applications, including research on time-series data, ML-based vectoring, and Embeddings (as Transformers, TGNN, TSFM, Graph Transformer, GNN, CNN, etc.)
Proficiency in Python (Pytorch, Pandas, NumPy, PyG - nice to have), and Applied Science SDLC - Discovery, Research, development, fidelity, deployment, monitoring, Training, and fine-tuning
Experience in anomaly detection, abnormal behavior, outliers, pushing recall, precision, and tail metrics KPIs boundaries
Experience working with ML infrastructure such as MLFlow, Vertex AI, Sagemaker etc.
The ability to translate research into scalable, production-ready solutions.
Experience working on Agile teams with a passion for fast iterations, feedback, and continuous learning.
Proven ability to collaborate with diverse, cross-functional groups, including product managers, infrastructure, and data engineering teams.
Experience in feature engineering-based signal processing - a big advantage.
This position is open to all candidates.