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At NetWitness, we believe in challenging the established mindsets, approaches, and product categories in the information security industry. Every product that we deliver to market is based on a core set of principles grounded in the major paradigm shifts in play and the implications that they have for our customers. Do the right thing – by our customers, employees, and shareholders...think long-term, but act with a sense of urgency. What we do matters – our work makes a difference in the world. We give a damn – about our customers, about what we’re doing, about each other...we’re in this together. We are a fun company – building cool products with technical insight that help our customers solve meaningful problems. Our mission is delighting our customers with everything we do. We provide thousands of customers around the world with essential security capabilities, leading with our Intelligence Driven Security Strategy and Vision, to protect their most valuable assets from cyber threats. With NetWitness’s award-winning products, organizations effectively detect, investigate, and respond to advanced attacks; reduce IP theft and cybercrime.
Senior Software Engineer - Machine Learning
Location
Turkey
Posted
73 days ago
Salary
0
Seniority
Senior
Job Description
Senior Software Engineer - Machine Learning
Partner One Capital
About SafeGraph SafeGraph is a Data as a Service (DaaS) company with one focus: curating the most accurate, precise, and fresh points of interest (POI) database on the planet. We provide product builders, data scientists, and analytics teams with the location data they need to power site selection, transaction enrichment, advertising audiences, competitive intelligence, and more. Our customers include companies like Plaid, Mapbox, Clear Channel — spanning fintech, retail, real estate, adtech, logistics, and government. We’re fully remote, lean by design, and serious about data quality. The Role You’ll be a generalist responsible for building and running large-scale data, machine learning, and agentic systems. The focus is operational ML/AI, including agentic systems and geospatial data pipelines. You should be comfortable owning the full lifecycle: from data ingestion and distributed processing to model development, deployment, and monitoring. This role requires the ability to iterate quickly from initial concept to a robust, production-ready solution. Key Responsibilities - Take ownership of the end-to-end AI/ML lifecycle, with a strong focus on dealing with complex and messy data, thorough evaluation of different approaches, and successfully deploying robust models, and handling cost vs performance tradeoffs. - Implement and integrate large-scale, agent-based systems with access to external systems, building these solutions from the ground up and integrating them with our existing infrastructure. - Establish observability for pipelines, models, and agents (metrics, tracing, alerting). - Collaborate with product and customer teams to drive revenue.
Job Requirements
- Strong experience with distributed data processing, particularly Spark and SQL.
- Proven expertise in building production machine learning systems, including working with large, wide datasets, effective training, deployment, and monitoring.
- Experience designing and deploying task-oriented AI agents and working with coding agents.
- Experience working with cloud services across data, compute, and ML.
- Strong communication abilities, including code architecture and documentation, at a level where any technical team member can troubleshoot and contribute easily.
- Languages: Scala, Python
- Tools / Frameworks: Spark, AWS Sagemaker / Bedrock, Kubernetes
- Nice to Haves
- Startup experience or growing projects from 0 to production in a larger org.
- Experience with large geospatial datasets, formats, and indexing strategies.
- Experience building operational AI agents that work at scale (millions of separate, complex tasks including web research)
- Experience with fine-tuning, distilling, and self-hosting LLM models.
- Experience in traditional ML, with a focus on working with messy data and robust evaluation of model approaches.
- Proficiency with CI/CD, infrastructure as code, and containerization.
- What Success Looks Like
- ML/AI models deployed with robust monitoring and significant customer impact.
- Agentic workflows improving internal/external operations.
- Infrastructure that is stable, observable, and automated.
- Successful iteration and delivery of new ML/AI products from concept to production.
- Ability to contribute to existing geospatial pipelines directly or through the use of AI
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Partner One CapitalAt NetWitness, we believe in challenging the established mindsets, approaches, and product categories in the information security industry. Every product that we deliver to market is based on a core set of principles grounded in the major paradigm shifts in play and the implications that they have for our customers. Do the right thing – by our customers, employees, and shareholders...think long-term, but act with a sense of urgency. What we do matters – our work makes a difference in the world. We give a damn – about our customers, about what we’re doing, about each other...we’re in this together. We are a fun company – building cool products with technical insight that help our customers solve meaningful problems. Our mission is delighting our customers with everything we do. We provide thousands of customers around the world with essential security capabilities, leading with our Intelligence Driven Security Strategy and Vision, to protect their most valuable assets from cyber threats. With NetWitness’s award-winning products, organizations effectively detect, investigate, and respond to advanced attacks; reduce IP theft and cybercrime.
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