Prisma Photonics, a fast growing start up, transforms infrastructure monitoring by leveraging optical fibers to monitor critical, large-scale systems like power grids and oil & gas pipelines across thousands of kilometers without the need for traditional sensors.

Our Hyper-Scan Fiber-Sensing™ technology, combined with advanced machine learning, empowers utility operators to achieve environmental and renewable energy goals while maintaining operational excellence on their path to net-zero emissions.

Founded in 2017, with offices in the U.S., Europe, and Israel (HQ), Prisma Photonics is led by an expert team with a proven track record in building and scaling successful companies within the lasers and deep-tech sectors.

We are seeking a talented, self-driven and passionate Deep Learning Engineer who will bring both deep learning expertise and engineering skills to our unique domain of Optical Fiber Sensing. In this role, you will balance cutting-edge ML research with the practical, large-scale data handling challenges that enable our solutions to thrive in the real world. About half of your day-to-day work will involve building and optimizing the data processing infrastructure and libraries that underpin our ML models.

What You’ll Do

• Design and implement custom data libraries and formats that support fast random access to massive real-time data streams. Work closely with the engineering team to ensure data pipelines are robust, scalable, and efficient.
• Leverage and extend data processing frameworks (e.g., Pandas, GeoPandas, Dask) to handle large-scale acoustic data. Write or customize Pandas extensions to meet specialized data modeling requirements.
• Spearhead core. deep learning initiatives to solve real-world challenges in detecting, classifying, and tracking spatiotemporal events. Push boundaries by inventing and applying novel ML and DL techniques tailored to our unique optical fiber domain
• Deliver well-tested, reliable, and maintainable code that seamlessly integrates into our rich and unique code infrastructure and ecosystem.
• Work alongside physicists, hardware engineers, data scientists, and field teams to gather requirements, plan real-world experiments, and collect critical data. Translate complex domain challenges into effective ML and data-engineering solutions.
• Harness advanced data analysis and visualization tools to uncover insights from diverse and voluminous real-world datasets.
• Continuously research new algorithms, technologies, and tools (both ML- and data-engineering–related) to keep Prisma Photonics at the forefront of innovation.
• Rapid prototyping, iterative experimentation, and fast-paced project turnovers are the norms. You’ll balance quick delivery with rigor and thoroughness.

What You Bring

• Advanced degree (M.Sc. or higher) in a relevant field (Computer Science, EE, Physics, or related).
• 3+ years of industry experience in roles involving DL related development and research.
• 3+ years of experience in software engineering roles.
• Expertise in Deep Learning & ML frameworks such as Pytorch, Pytorch Lightning, and familiarity with numerical libraries (NumPy, Pandas).
• Proven track record in solving novel DL challenges with strong algorithmic design skills.
• Solid Python programming skills and an ability to produce high-quality, production-ready code.
• Strong data handling and modeling skills; comfortable working with large and complex data structures.
• Excellent communication and teamwork skills—ability to collaborate effectively across technical disciplines.
• Adaptability to thrive in and contribute to a rich and unique code infrastructure and ecosystem.

Advantages

• Experience in writing Pandas extensions and working with Pandas extension libraries (e.g., GeoPandas, Dask).
• Publications in ML /DL and adjacent fields.
• Experience with seismic data and geophysics or handling massive temporal/geospatial data sets.
• Experience with Audio-based DL or related spatiotemporal data domains.
• Familiarity with DevOps and Big Data infrastructure for large-scale ML operations.
• Experience with tracking and estimation algorithms (e.g., Kalman filters, object tracking).

If you’re excited about pushing the envelope in both deep learning research and engineering data solutions for real-time acoustic fiber sensing—let’s talk! Join us and help build the technology that is reshaping infrastructure monitoring around the globe.