ML Engineer

CreatorIQ is the operating system for creator‑led growth trusted by more than 1,300 global brands and agencies. We’re on a mission to make businesses more human, and humans more impactful. Machine Learning Engineer, Applied AI As a MLE you’ll join our Product Innovations team and work across the full applied ML stack — deploying models, building evaluation systems, and making data and infrastructure decisions that turn experimental data science into cost‑efficient products. You’ll partner closely with our Data Science and Engineering teams on our vector embeddings ecosystem, ground‑truth pipelines, model evaluation, and pre/post‑processing decisions that determine product quality. What You’ll Do Deploy and monitor ML systems in production, from classic NLP and embedding models to LLM‑powered features – handling millions of records per day. Own the evaluation stack: golden datasets, model‑as‑a‑judge frameworks, inter‑annotator agreement, and regression tests that gate releases. Build and maintain our vector embeddings ecosystem and the retrieval, classification, and similarity patterns that sit on top of it. Partner with Data Science on annotation workflows, PII scrubbing, and ground‑truth pipelines. Improve our MLOps foundations—versioning, observability, drift detection—to enable faster shipping. Translate fuzzy product problems into measurable AI features with clear success criteria. What You’ve Done 4–7 years of professional software or ML engineering experience, including 2+ years shipping ML systems to production. Strong Python; comfort with the modern data/ML stack. Hands‑on experience deploying and monitoring models in at least one major cloud (AWS or GCP); willingness to learn the other. Production experience with NLP or ML systems—classification, NER, embeddings, ranking, similarity, or LLM‑powered features (a mix of traditional ML and LLM work is acceptable). Practical experience with evaluation for ML or LLM systems—golden datasets, model‑as‑a‑judge, IAA, precision/recall, or equivalent. Collaborative communicator who works well with data scientists and engineers, and can clearly explain ideas, requirements, and trade‑offs to non‑technical stakeholders. Bonus Experience with vector databases or retrieval systems at scale. Experience with managed ML services on AWS (SageMaker) and/or GCP (Vertex AI). Annotation workflow experience (Label Studio, Scale AI, or similar) and a point of view on inter‑annotator agreement. Familiarity with PII scrubbing patterns and privacy‑by‑design data handling. Open‑source contributions, blog posts, or talks on LLM/embedding production work. What You Will Get From Us People: work with talented, collaborative, and friendly people who love what they do. Guidance: utilize our learning platform to get the training and tools you’ll need to succeed from day one. Surprise meal stipends. Work/life harmony: 15 days vacation, floating and set holidays, wellness allowance, and paid parental leave. Whole Health Package: medical, dental, vision, life, disability insurance, and more. Savings: a 401(k) plan to help you plan ahead. Work‑from‑home stipend to set up a home office (or buy a new dog leash – your choice). Compensation Compensation Range: $132K – $165K. AI Transparency Notice We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications and note‑taking during interviews. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please refer to our Global Candidate Privacy Notice. Commitment to Diversity and Inclusion At CreatorIQ, we believe that diversity is the key to unlocking our full potential. We are committed to fostering an inclusive, equitable, and empowering work environment where everyone can thrive, regardless of race, ethnicity, gender, sexual orientation, age, religion, disability, or any other characteristic that makes us unique. #J-18808-Ljbffr CreatorIQ