---
title: 'Machine Learning Engineer at Teleskope'
canonical: 'https://feeny.ai/job/machine-learning-engineer-teleskope-new-york-xqrbsz9khfr5'
type: 'job'
last_seen: '2026-09-06'
---

# Machine Learning Engineer at Teleskope

- **Company:** Teleskope
- **Location:** New York, NY
- **Compensation:** $160k–$210k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-04-28
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/teleskope/eb4c9a90-07ee-41d6-a327-c3e3b7950274

## Job description

## About Teleskope

Teleskope is redefining data security for the AI era with the only dedicated platform that combines precise visibility with automated remediation. Teleskope continuously scans, catalogs and classifies data in-motion and at-rest while automating policy-based actions, helping organizations proactively manage data sprawl while securely enabling AI adoption.

Fresh off our $25 million Series A round, Teleskope is entering a high-growth phase backed by top-tier investors and exceptional product-market fit.

## About the role

We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity classification pipelines across varied data sources (text, documents, relational data, OCR, etc.). This role will bridge research experimentation and production implementation, helping evolve our current pipelines and advance toward our next generation element classification system.

This is a hybrid role requiring 3+ days in-office in New York City.

What You'll Do:

- Lead a team responsible for building, maintaining, and scaling production ML pipelines for entity extraction and data element classification across diverse data types.
- Partner with both analytics and ML-focused data scientists to translate experiments into deployed systems and unblock technical bottlenecks.
- Implement evaluation, monitoring, and regression testing frameworks in collaboration with QC.
- Drive incremental improvements to classification models and pipelines with a focus on measurable impact.
- Advocate for and implement best practices around model deployment, versioning, and operational monitoring.

About you:

- 4+ years of experience building and deploying ML systems in production.
- Strong experience with NLP systems and supervised entity classification models.
- Comfort moving from research prototypes to CI/CD and production pipelines.
- Proficiency in Python with common ML tooling.
- Strong analytical instincts and problem solving under ambiguity.
- Collaborative communicator who can partner across data science and engineering functions.

What you'll get:

- A high-impact role at an early-stage startup in a fast-growing market.
- Ownership over ML systems that directly power every customer workflow on the platform.
- An opportunity to contribute to core ML systems that power our classification service.
- A beautiful, well-stocked office in NYC’s Financial District.
- Flexible vacation and work from home days.
- Competitive salary and meaningful equity.
- Health, vision, dental, 401k and more benefits, heavily subsidized by Teleskope.

What We Value:

At Teleskope, we value strong engineers who build real systems. We look for team members who combine ML depth with pragmatic execution, take ownership of critical infrastructure, and ship reliable solutions that deliver real-world security and privacy outcomes.

## About Teleskope

## Company Overview
- **One-liner**: Teleskope provides an automated data security platform that uses a Data Reasoning Layer to detect, classify, and remediate sensitive data exposure in real time, enabling safe AI adoption.
- **Entity Type**: Private (Venture Capital-backed; Seed + Series A)
- **Headquarters**: New York, New York, USA
- **Founded**: 2022
- **Founders**: Elizabeth Nammour (Founder & CEO)

## Core Business
- **Primary industry**: Data security / cybersecurity
- **Target customers**: B2B; enterprise and mid-market organizations (e.g., fintech, financial services, media)
- **Mission or purpose**: To automate data security so teams can move fast while keeping data governed, especially as AI tools are adopted.

## Products & Services
- **Teleskope Platform**: An agentic data security platform that autonomously scans, catalogs, and classifies data in motion and at rest. It enforces remediation (block, quarantine, redact, notify, delete) natively without handoffs to third-party tools. The Data Reasoning Layer understands business context (e.g., chemical IP vs. hospital PHI) to reduce noise and enforce least-privilege access.

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: Total funding raised – $32.2M (Seed round in April 2024, Series A of $25M in November 2025)
- **Notable Investors/Partners**: M13, Primary Venture Partners, Lerer Hippeau (lead investors); also AirAngels, Correlation Ventures, CyLon Ventures, Essence Global
- **Growth Signals**: Trusted by organizations including Ramp, LegalZoom, Alloy, GoFundMe, and The Atlantic. The Atlantic reported a 95% reduction in time spent on data deletions. Headcount grew from ~29 (PitchBook) to 37 total employees (Built In), with 24 in product + tech roles.

## Competitive Advantages
- **Native remediation** – resolves exposure within the same platform (no SOAR handoffs), providing a full audit trail and reversibility.
- **Context-aware classification** – learns each organization’s unique risk profile and workflows, filtering out noise.
- **Speed and coverage** – two-second detection, 100% data coverage, 10x faster issue resolution than manual processes.
- **Agentic approach** – autonomously maps what AI tools and copilots can access, preventing sensitive data from reaching external LLMs.

## Strategic Focus
- **Enable responsible AI adoption** by giving security teams automated guardrails so employees can use AI tools without exposing sensitive data.
- **Reduce manual work** – shift security teams from alert triage to investigation and advisory by automating remediation and enforcing retention policies, cutting storage costs and legal exposure.

## Why Work Here
- **Culture**: Described as a place where people can do their best work and feel proud of the impact they make every day. Emphasis on building “more than software.”
- **Work policy**: Hybrid – team is on-site in New York City Tuesday through Thursday each week; 24/7 office access; employees encouraged to come in on Mondays and Fridays if they choose.
- **Tech stack**: Python, Go, TypeScript, React, Docker, Kubernetes, Terraform, AWS, Azure, GCP, PostgreSQL, Pandas, D3.js. Engineers work across the full stack.
- **Team size**: ~37 total employees, with 24 in product + tech (as of mid-2026).
- **Perks**: Modern NYC HQ, offsite events, and a collaborative engineering culture.

## Sources
1. [teleskope.ai](https://www.teleskope.ai/)
2. [teleskope.ai/company/careers](https://www.teleskope.ai/company/careers)
3. [builtin.com](https://builtin.com/company/teleskope)
4. [pitchbook.com](https://pitchbook.com/profiles/company/507341-89)

## Other roles at Teleskope

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- [Product Designer](https://feeny.ai/job/product-designer-teleskope-new-york-zf2mm7q28t99) — New York, NY
- [Founding Sales Development Representative](https://feeny.ai/job/founding-sales-development-representative-teleskope-new-york-5pphaqz92hk7) — New York, NY
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