Machine Learning Engineer

The Machine Learning Engineer will strengthen element and entity classification pipelines across diverse data sources, bridging research and production, with an in-office requirement in New York City.

Details

Location: New York, NY (hybrid). In-office requirement in New York City.

Compensation

USD 160,000 - 210,000 per year.

Responsibilities

• Oversee a team tasked with constructing, maintaining, and scaling production ML pipelines for entity extraction and data element classification across varied data sources.
• Collaborate with both analytics-focused and ML-oriented data scientists to convert experiments into deployed systems and resolve technical bottlenecks.
• Develop evaluation, monitoring, and regression testing frameworks in collaboration with Quality Control.
• Pursue incremental improvements to classification models and pipelines with measurable impact.
• Promote and implement best practices around model deployment, versioning, and operational monitoring.

Requirements

• Minimum of four years of hands-on experience building and deploying ML systems in production environments.
• Extensive experience with natural language processing systems and supervised entity classification models.
• Ability to transition from research prototypes to CI/CD enabled production pipelines.
• Proficiency in Python and common ML tooling.
• Strong analytical acumen and the ability to solve problems under ambiguity.
• Proven collaborator who can partner across data science and engineering teams.

Technologies

• Python

Benefits

• A high impact role at a growing early-stage startup in a dynamic market.
• Ownership of ML systems powering customer workflows across the platform.
• Opportunity to contribute to core ML systems underlying the classification service.
• A well-appointed office located in New York City's Financial District.
• Flexible vacation and work from home options.
• Competitive salary and meaningful equity.
• Health, vision, dental, 401k and additional benefits, heavily subsidized by Teleskope.

What We Value

At Teleskope, we value engineers who build robust systems, blend deep ML expertise with pragmatic execution, own essential infrastructure, and ship reliable solutions that deliver real-world security and privacy outcomes.