Machine Learning Data Engineer

Company Overview:

Cellebrite’s (Nasdaq: CLBT) mission is to enable its global customers to protect and save lives by enhancing digital investigations and intelligence gathering to accelerate justice in communities around the world. Cellebrite’s AI-powered Digital Investigation Platform enables customers to lawfully access, collect, analyze and share digital evidence in legally sanctioned investigations while preserving data privacy. Thousands of public safety organizations, intelligence agencies and businesses rely on Cellebrite’s digital forensic and investigative solutions-available via cloud, on-premises and hybrid deployments-to close faster and safeguard communities.

To learn more, visit us at www.cellebrite.com, https://investors.cellebrite.com/investors and find us on social media @Cellebrite.

Position Overview:

Join our AI SaaS Team and take a pivotal role in shaping the next generation of forensic AI solutions.

You’ll design and build the infrastructure, tools, and pipelines that empower our researchers and data teams to innovate faster and smarter.

In this role, you’ll work side-by-side with data scientists and AI researchers to transform ideas into reality — integrating multi-modal data, state-of-the-art machine learning models, and intuitive interfaces into scalable solutions.

You’ll also take ownership of AI/GenAI infrastructure and bring MLOps best practices into play, ensuring smooth data flows, efficient model training, and seamless deployments.

This is your chance to bridge research and engineering, influence cutting-edge products, and deliver impactful forensic insights to investigators worldwide.

Key Responsibilities

• Develop and maintain AI/GenAI infrastructure: training environments, pipelines, and data storage.
• Build scalable data pipelines for acquisition, transformation, and integration of multi-modal data.
• Support researchers by creating tools, visualizations, and prototypes for experiments and POCs.
• Collaborate with data scientists and engineers to operationalize AI models into Cellebrite’s SaaS products.
• Design and maintain cloud-native MLOps solutions for scalable deployments.

Requirements:

• 5+ years of hands-on software engineering (Python ecosystem a must).
• Solid understanding of AI/ML concepts and practical experience with ML libraries (PyTorch, Hugging Face, Scikit-learn).
• 2+ years experience building MLOps pipelines (data collection, training, deployment).
• Familiarity with Databricks (advantage).
• Experience with AWS (S3, EC2, SageMaker/Bedrock, Lambda).
• Hands-on work with databases: SQL, NoSQL, and vector stores.
• Knowledge of CI/CD practices and DevOps tools (Docker, Jenkins, GitHub Actions, Artifactory) — advantage.
• UI prototyping experience (Streamlit, Gradio, HTML/JS/CSS) — advantage.
• Familiarity with agentic AI frameworks (LangChain, PydanticAI, Google AI SDK) — advantage.

Why Join Us?

Help us bridge research and engineering to build next-generation AI-powered solutions that accelerate investigations and deliver meaningful impact worldwide.

You will work with top AI, Data and Engineering talents, cutting-edge technologies, and a dynamic, collaborative team.