Machine Learning Jobs in Washington DC

Positions 25,833 Updated daily

Looking for Machine Learning jobs in Washington DC? Browse our curated listings with transparent salary information to find the perfect Machine Learning position in the Washington DC area.

Thermite Welder - RAILROAD EXPERIENCE REQUIRED

Company: RailWorks Corporation

Location: Washington State

Posted Sep 09, 2025

RailWorks also offers opportunities to grow your career, develop your skills and pursue success. Works outdoors at railroad construction sites.

Staff Nurse

Company: Kaiser Permanente

Location: Tacoma, Washington

Posted Aug 17, 2025

Marketing Product Manager

Company: Aquent Talent

Location: Washington State

Posted Aug 18, 2025

Implement SEO best practices and optimize for AI-driven answer engines (GEO). Bachelor’s Degree in Business, Marketing, Communications, or a related field AND 8…

Frequently Asked Questions

What are typical salary ranges by seniority for machine learning roles?
Entry‑level ML Engineer: $90k–$120k; Mid‑level ML Engineer or Data Scientist: $120k–$160k; Senior ML Engineer or Research Scientist: $160k–$220k; Lead ML Engineer or Principal Research Scientist: $200k–$280k; AI Product Manager: $130k–$180k depending on experience and market.
What skills and certifications are most valuable in machine learning today?
Core language: Python; Deep learning frameworks: TensorFlow, PyTorch; Scikit‑learn for classical models; SQL and NoSQL databases for data ingestion; Docker and Kubernetes for deployment; Cloud AI services such as AWS SageMaker, GCP Vertex AI, Azure ML. Certifications: TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, GCP Professional Machine Learning Engineer.
How common is remote work for machine learning positions?
Over 70% of ML roles allow full remote or hybrid arrangements. Startups and fintech firms tend to offer 100% remote options, while larger enterprises often provide hybrid models with occasional on‑site data‑center visits. Remote work is especially prevalent for roles focused on model training and research.
What career progression paths exist in machine learning?
Typical paths: ML Engineer → Senior ML Engineer → Lead ML Engineer → ML Manager; Data Scientist → Senior Data Scientist → Lead Data Scientist → Head of Data; Research Scientist → Senior Research Scientist → Principal Scientist → Chief Data Scientist; ML Ops Engineer → Senior ML Ops Engineer → Lead ML Ops Engineer → Director of MLOps. Progression often involves moving from coding to architecture, then to leadership and strategy.
What are the current industry trends shaping machine learning hiring?
Key trends: reinforcement learning for autonomous systems; federated learning for privacy‑preserving models; edge AI for IoT devices; AutoML platforms speeding model deployment; MLOps practices for scalable pipelines; explainable AI and ethics compliance; and increased demand for AI governance roles.

Related Pages

© 2026 Job Transparency. All rights reserved.