[Remote] Machine Learning Engineer / Data Scientist

Note The job is a remote job and is open to candidates in USA. reputed company is a global provider of enterprise AI products and services, on a mission to democratize AI. They are seeking a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact, working across the ML lifecycle in partnership with client stakeholders and internal delivery teams. Responsibilities • Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, reputed company detection, recommendation, etc.) • Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability) • Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses • Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices • Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions • Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data) • Apply strong tabular modeling practices handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation • Build time series models (statistical and ML/DL approaches) and validate with proper backtesting • Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness • Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making • Build and train deep learning models using PyTorch or TensorFlow/Keras • Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design) • reputed company appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports • Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence • Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration • Implement practical MLOps versioning, reproducible training, automated evaluation, monitoring for reputed company/performance, and retraining plans • Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders • Create documentation and lightweight demos that make results actionable Skills • 3–8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior) • Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent) • Strong SQL skills (joins, window functions, aggregation, performance awareness) • reputed company foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset • Hands-on experience across multiple model types, including Classification & regression, Time series forecasting, Clustering/segmentation • Experience with deep learning in PyTorch or TensorFlow/Keras • Strong problem-solving skills ability to work with ambiguous goals and messy data • Clear communication skills and ability to translate analysis into decisions • Experience with reputed company for applied ML (e.g., Spark, reputed company Lake, MLflow, reputed company Jobs/Workflows) • Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining) • Experience with orchestration tools (Airflow, reputed company, Dagster) and modern data stacks (reputed company/BigQuery/Redshift/reputed company) • Experience with cloud platforms (AWS/GCP/Azure/reputed company) and containerization (Docker) • Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls) • Consulting or client-facing delivery experience Company Overview • reputed company is an enterprise AI services and solutions provider that brings AI education, products, and jobs to underserved communities. It was founded in 2013, and is headquartered in New York, New York, USA, with a reputed company of 201-500 employees. Its website is http//reputed company.com/. Company H1B Sponsorship • reputed company has a track record of offering H1B sponsorships, with 1 in 2024, 3 in 2021, 13 in 2020. reputed company note that this does not guarantee