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ML Engineer

Bangun dan monitor sistem ML yang dapat diandalkan untuk jutaan catatan sehari

Sebagai ML Engineer di CreatorIQ, kamu akan bekerja di seluruh stack ML terapan, mulai dari deploy model hingga membangun sistem evaluasi. Kamu akan bekerja sama dengan tim Data Science dan Engineering untuk memastikan sistem ML berjalan dengan baik di skala besar, terus dievaluasi, dan terus berimprovisasi. Kamu akan fokus pada produk yang berorientasi pada produksi dengan peluang untuk riset.

Kenapa Menarik?

CreatorIQ adalah perusahaan yang diakui secara global dan memiliki budaya kerja yang fleksibel

Tanggung Jawab Utama

  • Deploy dan monitor sistem ML di produksi, termasuk model NLP klasik dan fitur berbasis LLM
  • Mengembangkan dan memelihara stack evaluasi untuk memastikan model ML berfungsi dengan baik
  • Membangun ekosistem vector embeddings dan pola pengambilan, klasifikasi, dan kesamaan yang berdasar pada itu
  • Bekerja sama dengan tim Data Science dan Engineering untuk memastikan kualitas produk

Persyaratan

  • Pengalaman dalam deploy dan monitoring sistem ML
  • Kemampuan untuk membangun dan memelihara sistem evaluasi ML
  • Pemahaman mendalam tentang vector embeddings dan pola pengambilan data
  • Kemampuan untuk bekerja sama dengan tim Data Science dan Engineering

Skills Wajib

machine learningpythonmachine-learningnlpdata-sciencevector-embeddings

Konteks Indonesia

Overlap Jam Kerja:
Fleksibel — atur jam kerjamu sendiri
Lihat selisih gaji remote (USD) vs lokal →

Keywords

machine-learningml-engineernlpdata-sciencevector-embeddingsfull-timeremote-region
Lihat Deskripsi Asli dari Ashby Job Boards

Deskripsi asli dari Ashby Job Boards

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. We operate by our values — be intentional, pursue excellence every day, embrace the journey together, and be a good human — every day. CreatorIQ has earned the title of best companies to work for in multiple programs, including BuiltIn LA and NY. It’s been named a Fastest-Growing Company in North America on the Deloitte Technology Fast 500™ for four years, was named a leader in IDC MarketScape: Worldwide Influencer Marketing Platforms for Large Enterprises in 2025, was named a Leader by The Forrester New Wave™: Influencer Marketing Solutions, and has been consistently recognized by G2 as a Leader, and is rated 5 stars on Influencer MarketingHub. We operate in a flexible work model that combines both in-person and remote work to boost collaboration, enhance innovation, and adapt to individual work styles. We're seeking passionate, innovative minds to join our journey. Be a part of our dynamic team and let's transform the industry together! 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 the evaluation systems that tell us whether they actually work, and making the 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 the pre/post-processing decisions that determine product quality. This is a production focused role, with some research opportunities. You'll be the engineer who makes sure our ML systems - both traditional NLP and embedding models and our LLM-powered features - work reliably at scale (millions of records per day), are continuously evaluated against ground truth, and improve over time. What you'll do - Deploy and monitor ML systems in production, from classical NLP and embedding models to LLM-powered features - where "production" means 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 - so the rest of the team can ship faster - 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 (most candidates have done some mix of traditional ML and LLM work; we care that you've shipped, not which camp you came up in) - Practical experience with evaluation for ML or LLM systems - golden datasets, model-as-a-judge, IAA, precision/recall, or equivalent. You don't need to have built one from scratch, but you should know why they matter and how to improve them - Collaborative communicator - you work well alongside data scientists and engineers, and can clearly explain ideas, requirements, and tradeoffs 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 Confidence can sometimes hold us back from applying for a job. But we'll let you in on a secret: there's no such thing as a 'perfect' candidate. Have 50% of the criteria? Excited about this opportunity? Passionate about what we do at CreatorIQ? Please apply! CreatorIQ is a place where everyone can grow. 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 fully get the training and tools you’ll need to become successful here from your first day with us. - Surprise meal stipends: work from home can’t stop the enjoyment of someone else making a meal for you! - 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 401k (USA) plan to help you plan ahead. - Work from home stipend: to assist you in setting up a home office that works for you (or buy a new dog leash - your choice!). Who we are: CreatorIQ is the operating system for creator-led growth. Trusted by more than 1,300 global brands and agencies—including Burson, Delta Air Lines, Google, LVMH, Nestlé, and Sephora—CreatorIQ unifies creator marketing across paid, owned, earned, commerce, and community into one seamless, enterprise-grade ecosystem. With industry-leading intelligence infrastructure, rigorous compliance and security standards, and integrations with Meta, Snapchat, TikTok, YouTube, and more, CreatorIQ empowers brands and agencies to harness the creator economy as a strategic growth engine. CreatorIQ is a global company headquartered in Los Angeles with offices in Austin, New York, San Francisco, London, Manila, and Warsaw. Learn more at http://www.creatoriq.com/www.creatoriq.com http://www.creatoriq.com and follow us on LinkedIn https://www.linkedin.com/company/creatoriq and Instagram https://www.instagram.com/creatoriq. 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. By embracing our core values of being intentional, pursuing excellence every day, embracing the journey together, being a good human, and staying focused on what’s important, we create an atmosphere that promotes collaboration and growth. Join us to celebrate differences, innovate together, and be a part of a business that is disrupting the marketing industry. Compensation, benefits, and beyond: We understand that a comprehensive benefits package plays a significant role in your overall compensation. To gain more insight into the various components of our total compensation, we invite you to review our benefits and perks https://creatoriq.notion.site/What-you-ll-get-from-us-at-CreatorIQ-d252de0c5995417f89b564cfdbbc4b24?pvs=4. 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 https://creatoriq.notion.site/Global-Candidate-Privacy-Notice-1f29bdd3fbd98069a1e2eb6acefb3acf.

Konteks Gaji

Posisi Engineering serupa di LokerDollar dibayar sekitar $168.75k/yr (kisaran $11.194k–999.999k/yr, dari 376 listing aktif).

Perekrutan di CreatorIQ

CreatorIQ punya 15 lowongan aktif lain di LokerDollar dan telah merekrut di sini sejak 4 Jul 2026 — di kategori Engineering, Marketing, Data & Analytics.

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Perusahaan
CreatorIQ
Sumber
Ashby Job Boards
Gaji
Tipe Pekerjaan
full time
Lokasi
Remote
Kategori
Level
unspecified
Diposting
4 Jun 2026

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Apakah ML Engineer di CreatorIQ bisa dikerjakan remote?
Posisi ini berlokasi di Remote. Detail remote/onsite ada di deskripsi lowongan.
Berapa gaji untuk ML Engineer di CreatorIQ?
Rentang gaji yang tercantum untuk posisi ini adalah $132k–165k/yr.
Jenis pekerjaan apa ML Engineer di CreatorIQ?
Posisi ini adalah pekerjaan full time.
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