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.

Aerospace Machinist

Company: Confidential-Manufacturing

Location: Washington State

Posted Aug 08, 2025

They do their own coolant and oil checks. Manual tool offsets, reading micrometers, putting parts on fixtures. Brand new DMG Mori 5 axis machine.

Patient Counseling / Clinical Pharmacist

Company: Advanced RX

Location: Fort Washington, PA

Posted Aug 08, 2025

Ability to focus more on clinical information/patient care. Counsel patients over the phone on their compounded medications (minimal face-to-face interactions).

FINISH PROCESSOR LEVEL 2

Company: Confidential-Manufacturing

Location: Washington State

Posted Aug 04, 2025

Perform random tests on bonding and lamination processes and work with feeder/engineering personnel to develop new processes and the sequence of operations.

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.

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