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.

Senior Associate, Data Science - People Analytics

Company: Capital One

Location: Washington DC

Posted Mar 01, 2025

Capital One is seeking a Senior Associate Data Science specialist for their People Strategy & Analytics team. The role involves applying data science and machine learning to understand associate behavior and inform talent strategies. The ideal candidate should be passionate about human capital, innovative, creative, technically skilled, and statistically minded. They should have a degree in a quantitative field and experience in data analysis, open-source programming, machine learning, and relational databases. Preferred qualifications include a master's degree in a STEM field, AWS experience, and proficiency in Python, PyTorch, Scala, or R.

Package Consultant-SAP SCM MM

Company: IBM

Location: US Washington

Posted Feb 27, 2025

As an IBM Associate Business Consultant, you will have the opportunity to tackle complex business problems, capitalize on market opportunities, and understand leading technologies. Your role involves learning consulting skills, translating client needs into business requirements, and working in an agile collaborative environment. You will be responsible for designing, developing, and integrating complex application components using various tools. The role requires a high level of resilience, strong analytical skills, and excellent interpersonal skills. IBM offers positions in Washington DC Metro Area, Hampton VA, and candidates must be willing to travel up to 100% and obtain a Federal security clearance.

Senior Associate, Data Scientist - Customer Management

Company: Capital One

Location: Washington DC

Posted Mar 01, 2025

Capital One is seeking a Senior Associate Data Scientist for the Mainstreet Customer Management Data Science team. The role involves partnering with cross-functional teams to deliver data-driven solutions, leveraging a broad stack of technologies including Python, Conda, AWS, H2O, and Spark. The ideal candidate should be creative, innovative, technically skilled, and statistically-minded. Basic qualifications include a Bachelor's or Master's degree in a quantitative field, with relevant experience in data analytics. Preferred qualifications include a STEM degree, AWS experience, and at least 2 years of experience in Python, machine learning, and SQL.

Managing Director: Federal Sales- IRS/Treasury

Company: IBM

Location: US Washington

Posted Feb 27, 2025

The role of a Technology Sales Managing Director at IBM involves leading a team of multiskilled professionals to craft and execute account strategies, helping clients navigate complex technology architecture decisions, and driving revenue growth. The position requires executive presence, technology expertise, and deep market knowledge. The individual will work with multiple teams and leaders across Sales, Consulting, and third-party seller Partners to develop and execute strategies that consistently deliver revenue growth. IBM offers excellent onboarding training and ongoing development opportunities. The sales environment is fast-paced and supportive, with a focus on teamwork and client relationships. The role involves technical and industry expertise, account planning, stakeholder management, sales strategy execution, and client engineering engagements.

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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