Machine Learning Jobs in Washington DC

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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.

Software Engineer-Mid

Company:

Location: Washington, DC

Posted Feb 03, 2025

Program Manager- Top Secret Clearance

Company:

Location: Washington, DC

Posted Feb 03, 2025

Program Planning and Control Analyst

Company:

Location: Washington, DC

Posted Feb 03, 2025

Sr UX/UI Designer (TS SCI Clearance)

Company:

Location: Washington, DC

Posted Feb 03, 2025

Sr. JAVA Developer

Company:

Location: Washington, DC

Posted Feb 03, 2025

ALM Actuary

Company: MassMutual

Location: Washington DC

Posted Feb 03, 2025

MassMutual is seeking a passionate and experienced actuary to join their Annuity ALM & Hedging team. The role involves owning all components of ALM for retail income annuities and institutional business, including business relationships, production, and ad-hoc analysis. The individual will also assist in cross-company initiatives and maintain ALM processes. The ideal candidate will have a Fellow of the Society of Actuaries (FSA) or Chartered Financial Analyst (CFA) designation, 7+ years of experience in actuarial business functions and risks, investments, ALM, or hedging, and proficiency in programming languages and actuarial software products. The role offers opportunities for continuous learning, mentorship, and networking within the organization.

Banking Fraud Business Analyst

Company: Robinhood

Location: Washington, DC / Remote

Posted Feb 03, 2025

Sr Solutions Architect-TS/SCI Required

Company:

Location: Washington, DC

Posted Feb 03, 2025

Information Security Consultant - Application Security Engineer

Company: MassMutual

Location: Washington DC

Posted Feb 03, 2025

MassMutual is seeking an experienced Application Security Engineer to join their dedicated team. The role involves driving security best practices, conducting in-depth security assessments, and collaborating with various teams to integrate security into the software development lifecycle. The ideal candidate should have a strong background in secure software development, knowledge of application security vulnerabilities, and experience with security tools. The company values collaboration, continuous learning, and innovation.

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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