Is the Machine Learning Engineer position at Create Music Group fully remote?

Yes, this Machine Learning Engineer position at Create Music Group is a remote position. The role is available for candidates in United States.

Is this a full-time or part-time Machine Learning Engineer role?

This is a full-time Machine Learning Engineer position at Create Music Group.

What are the main requirements for the Machine Learning Engineer role?

Key requirements include: 4+ years of software engineering experience in a production environment, with exposure to ML or data science work, Strong proficiency in Python and ML frameworks (PyTorch, scikit-learn, XGBoost, or similar), Hands-on experience building, deploying, and maintaining ML models, and more.

What is the salary range for the Machine Learning Engineer position?

The salary range for this Machine Learning Engineer role is $160k - $200k.

How do I apply for the Machine Learning Engineer position at Create Music Group?

You can apply for this Machine Learning Engineer position by clicking the "Apply Now" button on this page, which will take you to Create Music Group's application portal.

Machine Learning Engineer at Create Music Group

United States

$160k - $200k

Apply Now

Remote Opportunity

Machine Learning Engineer

Join Create Music Group as a mid professional working remotely from United States. Explore the role, benefits, and apply in one place.

Machine Learning Engineer

Create Music Group

Full Time

$160k - $200k

7 months ago

Job Summary We are building CreateOS — a next-generation operating system for modern record labels — and AI is at the center of it. As a Machine Learning Engineer, you will be a core builder on the team responsible for designing, training, deploying, and maintaining the ML systems that power…

United States

Mid

Python

PyTorch

SciKit-Learn

+5 more

Job Description

Job Summary

We are building CreateOS — a next-generation operating system for modern record labels — and AI is at the center of it. As a Machine Learning Engineer, you will be a core builder on the team responsible for designing, training, deploying, and maintaining the ML systems that power intelligent automation, forecasting, anomaly detection, and agentic workflows across the platform.

This is a hands-on engineering role for someone who is equally comfortable prototyping a new model and shipping it to production. You will work directly with the VP of AI & ML Engineering and partner closely with Data Engineering, Analytics, and Product to move AI from experimentation into reliable, scalable production systems embedded in real user workflows.

Your immediate impact will be on three of CMG's highest-priority AI initiatives: M&A catalog valuation forecasting, AI-driven A&R discovery, and marketing automation agents — each directly tied to revenue growth and competitive differentiation.

Responsibilities

Applied Machine Learning

Build and maintain ML models for forecasting, anomaly detection, classification, ranking, and optimization across music industry use cases (catalog valuation, royalty reasoning, A&R intelligence, marketing performance, etc.)
Partner with Analytics & BI to identify, engineer, and validate features that drive meaningful predictive power
Own the full ML lifecycle — from problem framing and data exploration through training, evaluation, deployment, and monitoring

MLOps & Production Engineering

Deploy and monitor models in production using modern MLOps tooling
Instrument models for performance tracking, drift detection, and continuous improvement
Implement CI/CD, automated testing, model versioning, and observability for all ML systems
Collaborate with Data Engineering to ensure data quality, feature delivery, and pipeline reliability

Agentic AI & LLM Systems (Stretch)

Develop and maintain modular AI agents that automate multi-step workflows across CreateOS (contracts, accounting, distribution, metadata)
Build and iterate on RAG pipelines, retrieval architectures, and semantic search systems grounded in structured business data
Implement guardrails, evaluation frameworks, and safe action boundaries for agentic systems

Collaboration & Communication

Translate business problems from non-technical stakeholders into well-scoped ML solutions
Document model design decisions, evaluation results, and known limitations clearly
Contribute to a culture of engineering rigor and responsible AI development
Other duties as assigned

Qualifications

4+ years of software engineering experience in a production environment, with exposure to ML or data science work (academic, professional, or project-based); OR 2+ years of experience specifically as an ML Engineer or Applied Data Scientist
Strong proficiency in Python and ML frameworks (PyTorch, scikit-learn, XGBoost, or similar)
Hands-on experience building, deploying, and monitoring models in cloud environments — GCP strongly preferred (AWS or Azure acceptable); familiarity with services such as Vertex AI, BigQuery, Cloud Functions, and Cloud Run is a strong plus
Solid understanding of modern ML techniques — supervised/unsupervised learning, time series forecasting, embeddings, ranking — and their mathematical foundations
Experience with LLMs and prompt engineering, including building RAG systems or LLM-powered features
Comfortable working with structured and unstructured data at scale
Strong communication skills with the ability to explain complex model behavior to non-technical audiences

Preferred Qualifications

MS in Machine Learning, Data Science, Business Analytics, Computer Science, Statistics, or a related quantitative field; OR 4+ years of experience as an ML Engineer or Applied Data Scientist in lieu of an advanced degree
Experience at a startup or high-growth technology company where you owned features end-to-end
Familiarity with agentic frameworks (LangChain, LangGraph, AutoGen, or similar)
Background in music, media, entertainment, or rights/royalties data
Experience with ontology design, knowledge graphs, or semantic data modeling
Contributions to open-source ML projects or published research
Familiarity with AI evaluation practices — hallucination detection, bias auditing, model explainability

Pay Scale

$160,000 - $200,000/USD per year
The final compensation within this range will be determined based on the candidate’s experience, skills, and overall fit for the role.

Fair Chance Policy

In accordance with the Los Angeles County Fair Chance Ordinance, we will consider employment for qualified applicants with criminal histories. We evaluate candidates based on their qualifications and the nature of the offense in relation to the job for which they are applying.

Requirements

4+ years of software engineering experience in a production environment, with exposure to ML or data science work
Strong proficiency in Python and ML frameworks (PyTorch, scikit-learn, XGBoost, or similar)
Hands-on experience building, deploying, and maintaining ML models
Ability to partner with Analytics & BI to identify, engineer, and validate features
Experience with MLOps & Production Engineering, including CI/CD, automated testing, model versioning, and observability
Collaboration with Data Engineering to ensure data quality, feature delivery, and pipeline reliability
Ability to document model design decisions, evaluation results, and known limitations clearly
Contribution to a culture of engineering rigor and responsible AI development

Skills

Python

PyTorch

SciKit-Learn

XGBoost

MLOps

CI/CD

Forecasting

anomaly detection

Ready to Apply?

Join Create Music Group today

Salary Range

$160k - $200k

Posted 7 months ago

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