ML Engineer confidential US ago

Position: ML Engineer confidential US 1h ago
# ML Engineer confidential Contract mid Hybrid Mc Lean , Virginia, USPosted 5 days ago##

Role Overview confidential is hiring a mid-level ML Engineer. This is a contract hybrid role, based in McLean. Part of confidential's Risk hiring, posted 5 days ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.## Salary Context Salary is not disclosed in this posting. Market median for Mid-level Risk roles is $100k-$136k (based on 83 comparable listings).

Many employers share specifics during the interview process or after an initial screen.## Resume Keywords to Include Make sure these keywords appear in your resume to improve ATS scoring

PythonSQLAWSKubernetes Apache Spark Airflow CI/CDSign up free to auto-tailor your resume with all these keywords and get a higher ATS score## Job description

Senior Machine Learning Engineer About the Role Join a high-impact Machine Learning Engineering team supporting critical decisioning platforms across a leading financial services organization. This team develops and scales production machine learning systems that power credit decisioning, fraud detection, risk assessment, and partner-facing applications.

As a Sr Machine Learning Engineer, you will work at the intersection of software engineering, cloud infrastructure, and machine learning. Partnering closely with Data Scientists, Product Managers, and Engineering teams, you will design, deploy, and scale machine learning solutions that deliver measurable business impact. This role is ideal for engineers who enjoy building cloud-native ML platforms, operationalizing models, and driving production excellence at enterprise scale.

Key Details
· Rate: $70–$75/hr
·

Location:

McLean, VA (Hybrid – Tuesday through Thursday onsite)
· Duration: 12+ Month Contract
· Interview Process:
One-round virtual interview via Zoom What You'll DoDesign, develop, and deploy production-grade machine learning solutions on AWSBuild and maintain scalable ML pipelines for model training, validation, deployment, and monitoring

Partner with Data Scientists to operationalize advanced analytical and machine learning models

Develop cloud-native infrastructure to support machine learning workloads

Optimize model performance, reliability, and operational efficiency

Implement best practices for testing, CI/CD, governance, and monitoring across the ML lifecycle

Support enterprise-scale machine learning initiatives across:
Credit Decisioning Fraud Detection Risk Assessment Partner and Acquisition Programs Contribute to the evolution of ML platform capabilities and engineering standards

Required Qualifications 5+ years of experience in Machine Learning Engineering, Software Engineering, or related disciplines

Strong proficiency in Python Deep expertise with AWS services, including ECS, EC2, EKS, S3, and cloud-native architectures

Experience designing and deploying machine learning applications in production environments

Hands-on experience with Kubernetes

Experience with workflow orchestration tools such as Kubeflow Strong understanding of MLOps principles and the machine learning lifecycle

Experience with distributed data processing frameworks such as Apache Spark Strong software engineering fundamentals, including version control, testing, and CI/CD practices

Preferred Qualifications

Experience with Databricks and modern analytics platforms

Strong SQL and data analysis experience

Experience building end-to-end machine learning platforms

Familiarity with feature stores, model monitoring, and ML observability toolsAWS Solutions Architect or related cloud certifications

Experience supporting large-scale enterprise machine learning ecosystems

Exposure to Generative AI, LLM deployment, or AI platform engineering initiatives Technical Environment Cloud & Infrastructure AWS (EC2, ECS, EKS, S3)
Kubernetes Docker Cloud -Native Architecture Machine Learning & MLOps Kubeflow Apache  Airflow Model Training & Deployment ML Pipeline Orchestration CI/CD Automation Model Monitoring & Governance Programming & Data Technologies Python Apache  SparkSQLPandas Num Py Databricks  Why Join Us?

Impact at Scale:
Your work will directly influence…