Senior Machine Learning Engineer – Scoring, Audience Models

Job not on LinkedIn

🔥 0 minutes ago

🇪🇺 Europe – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

iDelsoft

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

iDelsoft is a technology partner based in Tampa, specializing in software development and building dedicated teams for high-growth companies. They offer a range of services including custom application development and talent search, ensuring high-quality solutions that save businesses from costly disruptions. With a focus on startups and enterprises, iDelsoft aims to provide scalable and reliable technology solutions tailored to specific business objectives.

📋 Description

• Own account and lead scoring end to end, including target definition, label design, feature engineering, model selection, and calibration • Build lookalike and similarity systems to identify high-potential accounts and validate them against tuned baselines • Use Elasticsearch as a feature source and serving layer, including aggregations, vector search, and indexed model scores • Design leakage-free evaluation with decision-matched metrics, including lift, precision at k, calibration, and online experiments • Address entity resolution, deduplication, missingness, label noise, sampling bias, and feedback loops • Build training and inference pipelines, feature storage, batch scoring, and near-real-time scoring • Integrate scoring systems with Node.js services • Monitor production models for drift and degradation and retrain on a defensible cadence • Collaborate with product and engineering to surface scores in the application • Explain to customers what scores do and do not mean

🎯 Requirements

• 4+ years in machine learning or data science roles, including 2+ years shipping supervised models that drove real decisions in production • Formal grounding in machine learning, deep learning, and advanced statistics — a quantitative degree or equivalent rigorous training • Comfort with the mathematics of machine learning, not just APIs • Expertise in estimation and inference, sampling and selection bias, hypothesis testing and power, regularization and bias/variance, probability calibration, and causal versus correlational claims • Strong command of Python, scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow, pandas/Polars, NumPy, and SciPy • Experience extracting and aggregating features from large document stores at scale; readiness to work directly with Elasticsearch query DSL and aggregations • Experience with ranking, propensity, similarity, recommendation, or churn/conversion modeling • Ability to defend model targets, label provenance, validation limitations, and post-launch failures • Experience building ML foundations and infrastructure from an early stage • Engineering discipline with version control, testing, CI, and containers • Ability to hand a scoring service to a Node.js team • Nice to have: Elasticsearch dense_vector and kNN search, significant_terms, rank_feature scoring, index design, and query performance tuning • Nice to have: B2B data, GTM, martech, adtech, CRM enrichment, and firmographic data provider familiarity • Nice to have: approximate nearest neighbour search with pgvector, Qdrant, or FAISS • Nice to have: learning-to-rank, graph/network modeling, MLOps tooling, publications, competition track record, or open-source applied ML contributions

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume