[Remote] Machine Learning Consultant

Note: The job is a remote job and is open to candidates in USA. Brooksource is seeking an experienced Azure Cloud Specialist with strong expertise in Machine Learning, Data Engineering, and Recommendation Systems. The role involves supporting and extending data and ML infrastructure, owning end-to-end pipelines in Azure, and delivering high-quality recommender models for outcomes-focused applications. Responsibilities • Design, train, and tune recommendation models: collaborative filtering, content-based, and hybrid approaches • Implement and compare LightFM loss functions (WARP, BPR, logistic) and optimize for implicit vs. explicit feedback scenarios • Engineer features for user/item interactions, incorporate side features (user/item metadata), and address cold-start challenges • Build, optimize, and troubleshoot ETL/ELT pipelines using Azure Data Factory, Databricks (Spark), and Azure Storage services • Implement robust data preprocessing pipelines; manage train/test splits tailored to recommender data (e.g., time-based, leave-one-out) • Handle sparse matrices efficiently (e.g., using numpy, scipy) and scalable data flows for large interaction datasets • Establish hyperparameter tuning workflows (learning rate, epochs, regularization) and model versioning practices • Coordinate Azure resources and integrations across multiple systems for seamless data and model deployment (APIs, batch/stream) • Define and track evaluation metrics—precision@k, recall@k, AUC, coverage/diversity—through experiments and dashboards • Monitor model performance post-deployment; detect drift and trigger retraining when needed • Document technical decisions, configurations, pipelines, and model cards for transparency and reproducibility Skills • Strong Python fundamentals with numpy, pandas, scipy; familiarity with latent factor models, vector operations, dot products, and basic optimization • Hands‑on experience building recommender systems (collaborative/content‑based/hybrid) and working knowledge of LightFM (implicit/explicit feedback, WARP/BPR/logistic losses) • Practical experience in feature engineering, cold‑start handling, and sparse matrix workflows • Proven ability to develop and deploy ML models to production in Azure; strong pipeline skills with Data Factory, Databricks/Spark, and Azure Storage • Experience with train/test splitting for recommender data, hyperparameter tuning, and model versioning • Ability to work independently with minimal supervision in asynchronous environments; excellent communication skills • Experience with MLOps tooling and best practices (CI/CD for ML, model registry, experiment tracking) • Familiarity with API integration patterns (e.g., MuleSoft or similar) for serving recommendations • Prior work in education, workforce, or outcomes‑focused public sector systems Company Overview • Brooksource is a single source for project and supplemental support through contract employment, contract-to-hire labor employment. It was founded in 2000, and is headquartered in Indianapolis, Indiana, USA, with a workforce of 1001-5000 employees. Its website is Company H1B Sponsorship • Brooksource has a track record of offering H1B sponsorships, with 10 in 2020. Please note that this does not guarantee sponsorship for this specific role. Apply tot his job