Machine Learning Jobs in Washington DC

25,833 open positions · 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.

Site Reliability Engineer (Platform)

Company: Alarm.com

Location: Washington DC

Posted Jun 22, 2023

None Found

Analyst, Falcon Complete

Company: CrowdStrike

Location: Washington DC

Posted Jun 19, 2023

None Found

Partner Success Executive

Company: Alarm.com

Location: Washington DC

Posted Jun 21, 2023

None Found

Data Scientist

Company: Thomson Reuters

Location: Washington DC

Posted Jun 22, 2023

None Found

Industry Specialist - Digital Finance

Company: World Bank Group

Location: Washington DC

Posted Jun 20, 2023

None Found

Public Sector Finance AE

Company: Gartner

Location: Washington DC

Posted Jun 19, 2023

None Found

Technical Product Manager (Platform)

Company: Alarm.com

Location: Washington DC

Posted Jun 22, 2023

None Found

Customer Success Manager (Federal)

Company: Appian Corporation

Location: Washington DC

Posted Jun 20, 2023

None Found

Senior Mobile Build Engineer

Company: Alarm.com

Location: Washington DC

Posted Jun 22, 2023

None Found

VP, Product Management - Platform

Company: Cloudflare

Location: Washington DC

Posted Jun 22, 2023

None Found

Lead Software Engineer

Company: Two Six Technologies

Location: Washington DC

Posted Jun 21, 2023

None Found

Frequently Asked Questions

What are typical salary ranges for ML roles at different seniority levels?
Junior ML Engineers earn $90k–$120k annually, mid‑level engineers $120k–$160k, senior engineers $160k–$220k, and lead or principal ML roles can reach $220k–$300k+. In large tech firms, the upper end can exceed $350k when including equity, while early‑stage startups may offer lower base but higher stock options.
What skills and certifications are required for ML positions?
Core expertise includes Python, Jupyter, TensorFlow, PyTorch, scikit‑learn, and SQL. MLOps proficiency with Docker, Kubernetes, and cloud services (AWS SageMaker, GCP AI Platform, Azure ML) is essential for production roles. Certifications such as TensorFlow Developer, AWS Certified Machine Learning – Specialty, and Google Cloud Professional Machine Learning Engineer can validate knowledge and accelerate hiring.
Are ML jobs available for remote work?
Yes, many ML positions are fully remote or hybrid. Companies like Scale AI, Databricks, and Cohere offer remote‑first policies. Remote work requires high‑speed internet, secure VPN access, and collaboration via tools like JupyterHub, Slack, and Asana, but it also expands the geographic talent pool.
What career progression paths exist in ML?
Typical paths start as ML Engineer or Data Scientist, advance to Senior ML Engineer, Lead Data Scientist, or Research Scientist, then transition into managerial roles such as ML Manager, Director of AI, or VP of Data & AI. Progression hinges on building a strong portfolio, publishing research, mentoring junior teammates, and mastering cross‑functional skills like product strategy and ethics.
What are current industry trends shaping ML careers?
Edge AI and federated learning are driving demand for on‑device models; AutoML platforms reduce time to deployment; responsible AI frameworks (e.g., IBM AI Fairness 360) shape compliance roles; reinforcement learning is expanding into robotics; and interpretability tools like SHAP and LIME are becoming standard in regulated sectors such as finance and healthcare.

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