Fusemachines · 10 hours ago
Machine Learning Engineer / Data Scientist
United States
Full-time
Remote
Mid, Senior Level
3+ years expFusemachines 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 collaboration with client stakeholders and internal teams.
Artificial Intelligence (AI)Big DataMachine LearningSoftware
Responsibilities
Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly 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)
Choose 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 drift/performance, and retraining plans
Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
Create documentation and lightweight demos that make results actionable
Qualification
Required
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)
Solid 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
Preferred
Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
Consulting or client-facing delivery experience
Company
Fusemachines
Fusemachines is an enterprise AI services and solutions provider that brings AI education, products, and jobs to underserved communities.
201-500 employees
H1B Sponsorship
Fusemachines has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2024 (1)
2021 (3)
2020 (13)
Funding
Current Stage
Public CompanyTotal Funding
$9.87MKey Investors
Consilium Investment ManagementBusiness Oxygen (BO2)
2025-12-23Post Ipo Equity· $1M
2025-10-23IPO
2022-01-14Private Equity· $1M
Leadership Team
Sameer Maskey
Founder & CEO
Christine Chambers
Chief Financial Officer
Recent News
legacy.thefly.com
2026-01-21
2026-01-03
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