Senior Data Scientist

Capmont GmbH; United States; Remote; USD 120,000 - 200,000; Full time

Job summary

Plume is seeking a lead AI/ML Engineer to advance ML/LLM projects, clean and transform large telemetry datasets, and collaborate with engineering to deploy models in production. You will design feature engineering strategies, build models for anomaly detection and forecasting, and drive robust analytics pipelines.

Ideal candidates have strong Python and SQL skills, experience with AWS services like SageMaker, and a track record of delivering high-quality results under tight schedules.

Qualifications

• Experience leading, developing and owning AI projects.
• Strong experience with ML/LLM techniques and implementation.
• Strong programming skills in Python and experience with core data science libraries.
• Solid SQL skills for querying, aggregating, and joining complex datasets.
• Proven experience transforming messy, high-volume data into structured inputs for modeling.
• Deep understanding of feature extraction, selection, and transformation for predictive modeling.
• Strong grasp of statistics, probability, and applied machine learning.
• Ability to scope solutions and deliver high-quality results on tight timelines.
• Excellent communication and teamwork across engineering, product, and data functions.
• Experience in AWS cloud services (Sagemaker, S3).

Responsibilities

• Lead, develop, maintain and improve ML/LLM projects and other automations.
• Transform large-scale network and device telemetry data for modeling and analysis.
• Design feature engineering strategies to improve model accuracy and robustness.
• Use Python and SQL to explore data and build analytical pipelines.
• Translate product needs into analytical tasks and model development plans.
• Build and evaluate ML models for anomaly detection, forecasting, and optimization.
• Collaborate with engineering and product teams to deploy models to production.
• Balance experimentation with execution to deliver insights under tight schedules.
• Contribute to MLOps workflows for deployment, validation, and monitoring.

Skills

AI project leadership

ML/LLM techniques

Python programming

SQL for data

Data preprocessing

Collaborative skills

Model evaluation

Communication

Tools

Python

Pandas

NumPy

Scikit-learn

SQL

AWS SageMaker

Job description

Life at Plume

At Plume, we believe that technology isn't about moving faster, it's about making life’s moments better. Which is why we’ve built the world's first, and only, open and hardware-independent service delivery platform for smart homes, small businesses, enterprises, and beyond. Our SaaS platform uses WiFi, advanced AI, and machine learning to create the future of connected spaces—and human experiences—at massive scale.

We now deliver services to over 60 million locations globally and have managed over 3 billion devices on our platform. We’re expanding rapidly, pioneering a new category, and we achieved our Series F funding in just four years. Our customers include many of the world's largest Internet Service Providers (ISPs) who look to Plume to help them evolve their smart home offerings while gleaning insights from their own data.

With a bias for action and a love for being trailblazers, the team at Plume embodies a combination of relentless curiosity and imaginative innovation. We challenge ourselves to think in ways that other companies don't, work to do what should be done (rather than what can), and if we can’t do it exceptionally well, we don’t do it. It’s how we’ve assembled a team of world‑class builders, thinkers, and doers. And it’s how we’re reinventing what’s possible every day.

Responsibilities:

• Lead, develop, maintain and improve ML/LLM projects and other automations
• Manipulate, clean, and transform large-scale datasets of network and device telemetry for modeling and analysis.
• Design and implement feature engineering strategies that enhance model accuracy, interpretability, and robustness.
• Use SQL and Python (Pandas, NumPy, Scikit-learn, etc.) to explore data, build analytical pipelines, and deliver reproducible results.
• Translate product or business needs into well-scoped analytical tasks and model development plans.
• Build and evaluate machine learning models for anomaly detection, forecasting, and optimization.
• Collaborate closely with engineering and product teams to integrate models into production systems and monitor their performance.
• Balance experimentation with execution — delivering insights and models efficiently under tight schedules.
• Contribute to MLOps workflows for model deployment, validation, and monitoring.

Qualifications:

• Experience in leading, developing and owning AI projects
• Strong experience in ML/LLM techniques and implementation
• Strong programming skills in Python and experience with core data science libraries
  • Solid SQL skills for querying, aggregating, and joining complex datasets.
• Proven experience transforming messy, high-volume data into structured, high-quality inputs for modeling.
• Deep understanding of feature extraction, selection, and transformation for predictive modeling.
• Strong grasp of statistics, probability, and applied machine learning.
• Ability to understand requirements, scope solutions, and deliver high-quality results on tight timelines.
• Excellent communication and teamwork skills across engineering, product, and data functions.
• Experience in AWS cloud services (Sagemaker, S3, etc.)

About Plume

As the creator of the only open, hardware-independent, cloud-controlled experience platform for ISPs and their subscribers, Plume partners with over 400 ISP customers, including some of the world’s largest such as Charter, Liberty Global, and J:COM.

Using OpenSync, the most widely supported open-source, silicon-to-cloud framework for smart spaces, Plume’s software‑defined network allows ISPs to decouple their service offerings from hardware and rapidly curate and deliver new services over a multi‑vendor, open‑platform architecture.

Plume is an equal opportunity workplace that maintains a continuing policy of nondiscrimination in all employment practices and decisions, ensuring equal employment opportunities for all qualified individuals without regard to race, color, creed, religion, sex, national origin, age, physical or mental disability, sexual orientation, gender identity, marital status, pregnancy, childbirth or related individual conditions, medical conditions (as defined by state law), military or veteran status, or any other characteristic protected by federal, state or local law.