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ML Engineer

confidential
McLean, 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

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PythonSQLAWSKubernetesApacheSparkAirflowCI/CD

Job description

Senior Machine Learning EngineerAbout the RoleJoin 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 monitoringPartner with Data Scientists to operationalize advanced analytical and machine learning modelsDevelop cloud-native infrastructure to support machine learning workloadsOptimize model performance, reliability, and operational efficiencyImplement best practices for testing, CI/CD, governance, and monitoring across the ML lifecycleSupport enterprise-scale machine learning initiatives across: Credit DecisioningFraud DetectionRisk AssessmentPartner and Acquisition ProgramsContribute to the evolution of ML platform capabilities and engineering standards Required Qualifications5+ years of experience in Machine Learning Engineering, Software Engineering, or related disciplinesStrong proficiency in PythonDeep expertise with AWS services, including ECS, EC2, EKS, S3, and cloud-native architecturesExperience designing and deploying machine learning applications in production environmentsHands-on experience with Kubernetes Experience with workflow orchestration tools such as KubeflowStrong understanding of MLOps principles and the machine learning lifecycleExperience with distributed data processing frameworks such as Apache SparkStrong software engineering fundamentals, including version control, testing, and CI/CD practices Preferred QualificationsExperience with Databricks and modern analytics platformsStrong SQL and data analysis experienceExperience building end-to-end machine learning platformsFamiliarity with feature stores, model monitoring, and ML observability toolsAWS Solutions Architect or related cloud certificationsExperience supporting large-scale enterprise machine learning ecosystemsExposure to Generative AI, LLM deployment, or AI platform engineering initiatives Technical EnvironmentCloud & InfrastructureAWS (EC2, ECS, EKS, S3)KubernetesDockerCloud-Native ArchitectureMachine Learning & MLOpsKubeflowApache AirflowModel Training & DeploymentML Pipeline OrchestrationCI/CD AutomationModel Monitoring & GovernanceProgramming & Data TechnologiesPythonApache SparkSQLPandasNumPyDatabricks Why Join Us?Impact at Scale: Your work will directly influence credit decisions, fraud prevention, and customer experiences.Growth Potential: Be part of a rapidly expanding team with opportunities to convert to full-time.Collaboration: Work alongside top-tier data scientists and engineers in a supportive environment.Innovation: Access to modern ML tooling and cloud-native infrastructure. Senior Machine Learning Engineer | AWS | Kubernetes | Kubeflow | Airflow | Spark | Python | MLOps | Financial ServicesEverforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing® in Talent Satisfaction in the United States and Great Place to Work® in the United Kingdom and Mexico.Everforth Apex uses a virtual recruiter as part of the application process. Click here for more details. By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Everforth Apex and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at https://www.apexsystems.com/privacy-policyEverforth Apex Benefits Overview: Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our ‘Welcome Packet’ as well, which an Everforth Apex team member can provide.Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.If you require an accommodation under the Americans with Disabilities Act to participate in an interview with a virtual recruiter or to use our website for a search or application, please contact our Benefits Department at accommodations@apexsystems.com or 804-523-8228. Please note that this contact information is strictly to be used for medical ADA accommodations and that no other inquiries will be answered.UnitedHealthcare creates and publishes the Transparency in Coverage Machine-Readable Files on behalf of Everforth Apex Systems.

About confidential

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confidential

apexsystems.com

RiskHybrid

1 other open role at confidential on TryApplyNow.

Frequently Asked Questions

How do I apply for the ML Engineer position at confidential?

Use the Apply button above to submit your application directly to confidential. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Is the ML Engineer role at confidential remote or in-office?

This is a hybrid role based in McLean. Expect a mix of in-office and remote days, with the specific cadence set by the hiring manager.

What does a ML Engineer at confidential earn?

confidential has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the ML Engineer role at confidential posted?

This role was posted on July 6, 2026 (5 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.

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