Machine Learning Engineer
Posted 24 days ago · 0 applicants
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The role in plain words
This role involves joining a newly established engineering cell to develop, optimize, and deploy real-time machine learning systems. You will build recommendation algorithms and automation pipelines to process high-frequency time-series and sensor data from industrial machinery. Day-to-day tasks include fine-tuning models and collaborating with data scientists and infrastructure teams to integrate ML workflows into a distributed platform.
- B.Sc. in Computer Science, Data Science, Mathematics, Statistics, or a related exact science discipline
- 3+ years of proven professional experience operating as a Machine Learning Engineer, Deep Learning Engineer, or Applied AI Developer
- Expert-level programming mastery in Python, including deep familiarity with core mathematical and data libraries (NumPy, Pandas)
- Demonstrated track record of successfully deploying, monitoring, and scaling ML models in commercial production environments
Extracted from the job description · kept up to date automatically
Who this suits
This role suits candidates with a B.Sc. in a quantitative field and at least 3 years of professional experience deploying and scaling ML models in production. It is ideal for those with expertise in Python, NumPy, and Pandas, especially if they have experience with time-series or sensor data.
Full job description
Original listing · kept for referenceAn award-winning Industrial AI pioneer developing an autonomous manufacturing platform that transforms industrial production lines.
By deploying advanced smart manufacturing recommendation systems and decision-support engines, the company processes massive streams of industrial sensor data to minimize operational overhead, maximize efficiency, and drive predictive optimizations.
The company maintains an elite R&D workforce of 65 professionals, scaling its innovative footprint across global industrial sectors.
Located in Herzliya within short walking distance of the train station, the team operates primarily on-site to maintain tight cross-functional innovation, offering a structured hybrid model with Sundays as a permanent remote work day.
Position Overview-
• Machine Learning / Applied AI Engineer joining a newly established engineering cell to drive the development, optimization, and deployment of real-time ML systems.
• Shifting the balance toward robust development and production implementation, transforming complex theoretical frameworks and data science insights into highly scalable software components.
• Engineering intelligent recommendation algorithms and automation pipelines tailored to handle high-frequency, complex time-series and noisy sensor data generated by industrial machinery.
• Executing targeted model fine-tuning and building production-ready architectures optimized for low-latency decision-making environments.
• Collaborating closely with Data Scientists, Product Managers, and Core Infrastructure squads to embed ML workflows natively into the platform's distributed ecosystem.
• Core Stack & Ecosystem- Python, NumPy, Pandas, Machine Learning Engineering, Time-Series Analysis, Sensor Data Processing, Recommendation Systems, Model Fine-Tuning, and High-Scale Production Deployment.
Requirements-
• Academic Background: B.Sc. in Computer Science, Data Science, Mathematics, Statistics, or a related exact science discipline – Mandatory
• 3+ years of proven professional experience operating as a Machine Learning Engineer, Deep Learning Engineer, or Applied AI Developer – Mandatory
• Expert-level programming mastery in Python, including deep familiarity with core mathematical and data libraries (NumPy, Pandas) – Mandatory
• Demonstrated track record of successfully deploying, monitoring, and scaling ML models in commercial production environments – Mandatory
• Direct technical experience working with time-series data, digital signal processing, or IoT/sensor telemetry – Significant Advantage
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Hybrid
- B.Sc. in Computer Science, Data Science, Mathematics, Statistics, or a related exact science discipline, 3+ years of proven professional experience operating as a Machine Learning Engineer, Deep Learning Engineer, or Applied AI Developer, Expert-level programming mastery in Python, including deep familiarity with core mathematical and data libraries (NumPy, Pandas), Demonstrated track record of successfully deploying, monitoring, and scaling ML models in commercial production environments