Machine Learning Engineer
Ai Ml
Artificial Intelligence
Automation
Aws Solutions Architect
Cloud Infrastructure
Cloud Native
Cloud Operations
Cloud Platform
Cloud Platforms
Cloud Technology
Data & Ai
Data Analysis
Data Analytics
Data Engineer
Data Integration
Data Pipeline
Data Processing
Data Science
Database
DevOps
DevSecOps
Docker
Engineering
ETL
Informatica
Machine Learning Engineer
NLP
Platform Engineering
Programming Language
Programming Languages
Job Description
Factspan Inc is seeking a Machine Learning Engineer to own end-to-end analytics and deliver production-ready ML solutions. The role combines hands-on modeling with data engineering and stakeholder communication, supporting projects that start with data gathering and requirements and extend through processing, analysis, deliverables, and presentations.
This position is based in Seattle, WA (onsite) and is intended for an engineer with experience leading technical work and coordinating milestones across a team.
Key Responsibilities
- Work with large, complex datasets to tackle non-routine analysis problems using advanced analytical methods as needed.
- Perform end-to-end analysis, including data gathering from multiple storage platforms, requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Develop data pipelines that integrate different data sources.
- Plan project milestones, resourcing, and work distribution.
- Execute projects on schedule by analyzing risks and mitigating them.
- Lead a technical team of data scientists and engineers.
- Communicate project progress, challenges, results, and next action items to stakeholders.
Requirements
- 3-8 years of experience.
- Bachelor’s/Master’s Degree in Engineering, Statistics, or Mathematics.
- Excellent hands-on working knowledge of R, Python, advanced predictive modeling, SQL, and AWS.
- Hands-on expertise building machine learning models using R/Python and SQL, with deep experience in statistical methodology and statistical data analysis.
- Ability to set up environments on AWS and integrate multiple components into a complete solution.
- Experience using Google and Amazon NLP APIs to parse data and analyze outputs.
- Hands-on expertise with Amazon Docker tools to develop and deploy the solution.
- Proficiency in JAVA and Python.
- Understanding of topic modeling and supervised and unsupervised machine learning.
Technologies
- R
- Python
- SQL
- AWS
- Google NLP APIs
- Amazon NLP APIs
- Amazon dockers
- JAVA