Software Engineer I developing machine learning models and applications at Smart Data Solutions. Collaborating to improve infrastructure and automate processes using AI technology.
About the role
- Senior Machine Learning Engineer building and scaling core ML systems for data classification at Teleskope. Driving automated remediation and enabling GenAI features for data security platform.
Responsibilities
- Design, build, and own production ML systems that surface data risk and power automated remediation across the Teleskope platform.
- Develop agentic ML pipelines that combine detection, classification, and decision-making with automated, policy-driven remediation actions.
- Build and deploy NLP and GenAI models for:
- - Named Entity Recognition (NER) and sensitive data detection
- - Text, document, and table classification
- - Clustering, summarization, and risk prioritization
- - LLM-driven reasoning and remediation proposal workflows
- Define and implement quality, evaluation, and monitoring frameworks to ensure model correctness, stability, and safety in production.
- Collaborate with product and platform engineering to integrate ML systems into customer-facing features and workflows.
- Contribute to the architecture and evolution of Teleskope’s ML infrastructure, balancing velocity, reliability, and long-term maintainability.
- Serve as a senior technical contributor, influencing best practices and raising the bar for ML engineering across the team.
Requirements
- 6+ years of experience building and deploying machine learning systems in production, with a strong emphasis on NLP.
- Proven experience owning end-to-end ML pipelines, from data ingestion and preprocessing to deployment and monitoring.
- Hands-on experience with LLM-based systems, GenAI features, or agentic workflows in real-world applications.
- Strong software engineering skills, including:
- - Proficiency in Python
- - Experience building scalable services and pipelines
- - Experience with modern ML frameworks (e.g.,LangChain, HuggingFace) and production deployment patterns.
- Ability to reason about tradeoffs across accuracy, latency, cost, and system complexity.
- Strong communication skills and comfort collaborating across engineering, product, and customer teams.
- Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related field—or equivalent professional experience.
Benefits
- Health, vision, dental, 401k and more benefits, heavily subsidized by Teleskope.
- Flexible vacation and work from home days.
- Competitive salary and meaningful equity.
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