10a Labs is a research and advisory firm that helps technology companies address the negative externalities of the internet.

Industry: Research Services
Company Size: 11-50 employees

10a Labs

Savvy Admin PROD

**About 10a Labs: **10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.

10a Labs’ Investigations Team needs additional support to respond to critical safety incidents and conduct investigations across a range of abuse areas, including but not limited to Violence, Hate, Mental Health, CBRNE, Child Safety, Cyber Abuse and more.

**About The Role**

As a **Threat Investigator **, you will be supporting our Investigations Team and responsible for detecting and/or responding to malicious uses and abuse, investigating the activity, drafting reports based on your findings, and making recommendations. This will require technical experience investigating threat actors, harmful behaviors, and/or other activities; as well as a strong ability to use SQL and Python to query, transform, and understand data. You will also respond to escalations and reactive leads, including those that are not caught by our existing safety systems.

Investigations involve sensitive and distressing content, including sexual, violent, or otherwise-disturbing material.

**This role includes serving in an on-call capacity that will involve resolving urgent escalations outside of normal work hours, occasionally including evenings and weekends. ** The typical on-call rotation is 7 consecutive days per 2 months, though this may shift based on operational needs and candidates should be prepared to remain flexible.

This is a remote, full-time position.

**In This Role, You Will**

- Proactively detect and reacquire bad actors on our platform.

- Investigate potentially policy-violating activity by querying internal data sources (using SQL and Python) and cross-referencing open source information (OSINT).

- Document and share investigative findings with internal stakeholders.

**Requirements**

- At least 3+ years of related investigative experience in Trust & Safety, National Security, Defense, Intelligence, or Law Enforcement domains working on related topics; must be willing to work on sensitive subject matter including child safety.

- U.S.-based, with the ability to work West Coast hours (9am - 5pm PT).

- Ability to be on-call that will involve resolving urgent escalations outside of normal work hours, including occasional evenings and weekends.

- Strong SQL and Python proficiency and/or additional programming skills.

- Strong and applicable technical investigative skillset with ability to develop and maintain detection pipelines.

- Ability to rapidly context switch across domains, modalities, and abuse areas.

- Excited to work in a fast paced, ambiguous, and purposeful space with high impact across users and beyond.

**Preferred Qualities (but Not Required)**

- Expertise with risk and abuse related to AI platforms.

- Full professional proficiency in Arabic, Chinese, Farsi, Portuguese, Russian, or Spanish.

- Have experience scaling and automating detection and mitigation processes.

- Familiarity using language models to scale.

- Familiarity with one of the following topics/areas: violence, extremism,, child safety, digital mental health, scams and fraud abuse, radicalization/persuasion/grooming, hateful activities and groups.

Threat Investigator US

**About 10a Labs: **10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.

**In This Role, You Will**

- Design, implement, and optimize end-to-end data pipelines for scraping and processing structured and unstructured data using Google Cloud Platform (or similar) and best practices;

- Conduct ad hoc web scraping and data collection to support research and intelligence initiatives;

- Prepare data for further analysis, including data cleaning, transformation, anonymization, and masking;

- Contribute to the development of internal and external APIs, following best practices;

- Collaborate with ML engineers, other data engineers, and software developers to deliver actionable insights and functional tools, including internal and external dashboards, APIs, and data dumps; and

- Drive other critical initiatives.

**Requirements**

- Degree (or equivalent work experience) in Computer Science, Engineering, Information Science, Data Science or a related field (graduate degree preferred)

- 2+ years of professional experience in data engineering or a closely related field

- Ability to communicate complex technical ideas clearly to non-technical audiences

- Proficiency in Python, SQL

- Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy)

- Experience with Google Cloud Platform (or similar), including storage and database services (e.g., Cloud Storage, CloudSQL, Cloud Spanner) and workflow orchestration (e.g., Cloud Composer/Airflow, Cloud Run, Pub/Sub)

- Experience building and managing data pipelines, especially for text data

- Comfort working in fast-moving, high-impact environments, such as startups, AI research labs, or security-focused teams

**Compensation & Benefits**

- Salary Range: $105K–$125K, depending on experience and location

- Bonus: Performance-based annual bonus

- Professional Development: Support for conferences, continuing education, or leadership training

- Work Environment: Fully remote, U.S.-based

- Health Benefits: Comprehensive health, dental, and vision coverage

- Time Off: Generous PTO and paid holiday schedule

**Retirement: 401(k) plan **

Data Engineer, Web Scraping

**About 10a Labs: **10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.

**About The role: **We’re looking for an experienced ML engineer with a strong foundation in traditional ML and hands-on experience applying those skills to modern LLM systems. This is an applied role for someone who owns the full ML lifecycle—from data pipelines and model training to evaluation, deployment, and ongoing iteration in real-world production environments.

**At least 3–8+ Years of Industry Experience Required**

**In This Role, You Will**

- Build and deploy a multi-stage classification system optimized for high throughput and low latency, while ensuring high recall and precision.

- Integrate continuous feedback loops from human review to refine model performance.

- Design and implement real-world ML systems with a focus on robustness, observability, and scalability.

- Collaborate with researchers and SMEs to generate training data and test against edge cases.

- Work closely with a broader team of engineers to integrate ML components into production systems and ensure end-to-end system performance.

**We’re Looking For Someone Who**

- Has designed and deployed full ML pipelines (data ingestion → model training → evaluation → deployment → feedback).

- Comfortable working with noisy or adversarial real-world data, not just clean benchmarks.

- Understands the performance tradeoffs between recall, precision, latency, and cost—and knows how to tune for impact.

- Moves fast with strong instincts for where to prototype, where to systematize, and how to deliver models that hold up in production.

- Brings curiosity, creativity, innovation, and a bias for action in ambiguous environments.

**Requirements**

- At least 3–8+ years of professional working experience as a Machine Learning engineer, building, owning and deploying machine learning systems in production.

- Strong foundation in traditional ML techniques (e.g., clustering, anomaly detection, supervised learning).

- Hands-on experience with LLMs (e.g., OpenAI, Claude, LLaMA), including fine-tuning and prompt engineering.

- Proficiency in Python and modern ML / NLP tooling.

- Experience training models on small datasets and using in-context learning techniques.

- Familiarity with text processing pipelines, semantic embeddings, and vector search.

- Clear communicator of complex technical concepts to non-technical audiences.

- Experience deploying models in cloud environments (e.g., AWS, GCP).

- Experience designing or integrating human-in-the-loop systems for model evaluation or policy alignment.

**Nice To Have Experience With**

- Real-time ML pipelines.

- Scaled moderation or large-scale threat detection.

- Vision, audio, OCR, or deepfake classification.

- Designing multilingual embedding systems with code-switch detection.

- Agentic pipelines for explainable or rationale-based moderation.

- Rapid prototyping using modern LLM APIs and frameworks (e.g., OpenAI, Hugging Face, LangChain).

- Error analysis and model forensics—comfortable diving into false positives and failure modes.

**What Success Looks Like In The First 3 Months**

- You’ve designed and deployed a functioning moderation system using semantic embeddings and fine-tuned classifiers to detect abuse at scale.

- You've designed and refined at least one model evaluation pipeline, including precision / recall tracking and false positive analysis.

- You've contributed meaningful ideas to data strategy—synthetic generation, clustering schema, or policy alignment tuning.

- You’ve owned a full subsystem—from ideation to deployment—and seen it hold up under real usage and scrutiny.

**Compensation & Benefits**

- Salary Range: $150K–$250K, depending on professional experience, location, and other factors.

- Bonus: Performance-based annual bonus.

- Professional Development: Support for continuing education, conferences, or training.

- Work Environment: Fully remote, U.S.-based.

- Health Benefits: Comprehensive health, dental, and vision coverage.

- Time Off: Generous PTO and paid holiday schedule.

- Retirement: 401(k) plan.

Machine Learning Engineer

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