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About the Role
We are seeking a Data Scientist to join our AI & Data Science team. You will act as an internal AI consultant and technical lead, assisting various Sonatype teams in applying machine learning and generative AI to solve real-world challenges, including malicious behavior and anomaly detection, and developing GenAI experiences for developers and analysts. You will explore datasets, design experiments, build and validate models, and collaborate with experts to create scalable solutions, focusing on model development and deployment.
Responsibilities
- Lead applied AI projects from concept to impact, including prototyping, validation, and deployment of ML and GenAI solutions.
- Serve as an internal consultant to product, engineering, security, and research teams, defining problems, evaluating approaches, and advising on ML/AI best practices and generative technology usage.
- Lead the research, development, and deployment of models for use cases such as malicious behavior detection, anomaly detection, and fraud analysis, utilizing techniques from classical ML to LLMs, embeddings, RAG, and agentic workflows.
- Design robust experiments and establish evaluation pipelines for model reliability, accuracy, and business impact, including cross-validation, drift monitoring, and ground-truth evaluation.
- Translate research insights into scalable APIs, tools, or workflows to facilitate AI adoption by other teams.
- Explore new techniques like LLMs, embeddings models, RAG, and agentic workflows to improve developer and security experiences.
- Clearly communicate technical concepts, tradeoffs, and recommendations to diverse stakeholders through presentations, documentation, and collaboration.
- Mentor peers and enhance the organization's AI literacy and capabilities.
- Partner with the data governance team to ensure compliance with data-privacy regulations and ethical considerations when handling customer data.
Requirements
- 5+ years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.
- Computer Science or equivalent technical degree strongly preferred.
- Strong Python skills and practical experience with data and AI libraries/platforms such as Databricks, and LLM APIs, scikit-learn.
- Experience building and shipping ML or GenAI applications from prototype through to production.
- Deep familiarity with modern LLM ecosystems, including OpenAI, Anthropic/Claude, Hugging Face, and open-weight models.
- Ability to select models and design effective LLM applications using prompting, context management, structured outputs, retrieval, and tool use.
- Experience building agentic or multi-step AI workflows with LangGraph, LangChain, Semantic Kernel, or similar orchestration frameworks.
- Strong evaluation mindset: defining useful quality metrics, building representative evaluation datasets, assessing reliability, and making data-driven tradeoffs.
- Comfortable working with large, messy, structured, and unstructured data to produce features, insights, and clear visualizations.
- Proficiency with Git, testing, code review, and collaborative software-development practices.
- Practical, balanced judgment: comfortable exploring emerging AI capabilities while building maintainable, secure, dependable systems.
- Proactive and accountable, with strong written and verbal communication skills across technical and non-technical partners.
Skills
- Machine Learning
- Generative AI
- Python
- Databricks
- LLM APIs
- scikit-learn
- OpenAI
- Anthropic/Claude
- Hugging Face
- Open-weight models
- Prompting
- Context Management
- Structured Outputs
- Retrieval
- Tool Use
- LangGraph
- LangChain
- Semantic Kernel
- Git
- Testing
- Code Review
- Collaborative Software Development
- MLOps
- MLflow
- Experiment Tracking
- Reproducible Pipelines
- Model Versioning
- Application Versioning
- CI/CD
- Model Serving
- Production Monitoring
- Databricks ML
- AWS SageMaker
- Azure ML
- MCP
- Agent-Tool Integrations
- LLM Guardrails
- Production Safety Practices
- Copilot
- Claude Code
- Codex
- Cybersecurity
- Fraud Detection
- Anomaly Detection
- Code Analysis
- Software Supply-Chain Security
- PySpark
- Production Data Pipelines
- SaaS
Experience Level
- 5+ years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.
Education Level
- Computer Science or equivalent technical degree strongly preferred
Benefits
- Diversity & Inclusion Working Groups
- Parental Leave Policy
- Paid Volunteer Time Off (VTO)
About the Company
- Sonatype is the software supply chain management company that invented componentized software development and pioneered the software supply chain category.
- We are leaders in the open-source community and the DevSecOps industry, running the world’s largest repository of Java open-source components—Maven Central.
- Our platform empowers customers to rapidly create, deploy, and maintain innovative software at scale, aligning with business needs.
- Trusted by more than 2,000 organizations, including 70% of the Fortune 100, and over 15 million software developers.
- Our tools and guidance help deliver exceptional, secure software.
- We invented modern artifact management with Nexus Repository and introduced the world’s only solution that halts malicious open-source malware.
- We leverage AI/ML to provide clients, developers, and the industry with confidence in the quality, automation, and security of their software.
- Learn more at www.sonatype.com
Equal Opportunity
- We are an equal-opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- If you have a disability or special need that requires accommodation, please do not hesitate to let us know.