What is our mission?

Cellebrite’s (Nasdaq: CLBT) mission is to enable its customers to protect and save lives, accelerate justice, and preserve privacy in communities around the world. Cellebrite is a global leader in Digital Intelligence solutions for the public and private sectors, empowering organizations to master the complexities of legally sanctioned digital investigations by streamlining intelligence processes. Trusted by thousands of leading agencies and companies globally , Cellebrite’s Digital Intelligence platform and solutions transform how customers collect, review, analyze, and manage investigative digital data in legally sanctioned investigations.

What is your mission?

We are looking for a Research Scientist with expertise in ML/DL algorithms and technology development. The role will focus on pioneering data-driven solutions specifically for digital forensics and intelligence. The responsibility includes crafting and refining machine learning models to unveil actionable insights from intricate multimodal digital forensic data. As a central figure in our multifaceted research team, you will oversee projects from inception to fruition, guiding both initial data analysis and final model assessments. The ideal candidate will possess a rich analytical background, a history of innovative contributions in the domain, and a PhD or its equivalent. Strong leadership abilities and exemplary communication, both written and spoken, are paramount.

What are the requirements?

• PhD degree in Computer Science, or a related quantitative field.
• Strong proficiency in Machine Learning, Deep Learning, and Data Mining, including supervised and unsupervised learning, at least 7 years of experience.
• Proficient in Python and related data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, Matplotlib), at least 7 years of experience.
• Experience with Natural Language Processing (NLP) technologies.
• Excellent written and verbal communication skills in English.
• Ability to work in a dynamic, fast-paced startup-like environment.
• Experience with big data technologies such as Hadoop, Spark, or similar frameworks.
• Familiarity with cloud platforms like AWS, GCP, or Azure.
• Experience with platforms such as DataBricks/SageMaker.
• Experience with Graphs algorithms.