Mid Artificial Intelligence and Machine Learning Engineer jobs in United States
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Jobs via Dice · 21 hours ago

Mid Artificial Intelligence and Machine Learning Engineer

Jobs via Dice is seeking a Mid Artificial Intelligence and Machine Learning Engineer to develop and operationalize secure, scalable AI solutions. The role involves collaborating with cross-functional teams to modernize and operate AI-driven platforms, enhance data pipelines, and ensure compliance with security requirements.

Computer Software
badNo H1BnoteU.S. Citizen Onlynote

Responsibilities

As an experienced AI/ML Engineer, you will help develop and operationalize secure, scalable, production-grade AI solutions that sustain and advance mission-critical capabilities
You will work as part of a cross-functional team, collaborating with data engineers, data scientists, solution architects, and product owners to deliver high-impact AI/ML solutions across a broad range of use cases
In this role, you will modernize and operate an end-to-end, AI-driven platform built on Databricks, Palantir, Amazon Bedrock, and custom AI/ML models
You will sustain and enhance batch and streaming data pipelines, improve data quality, lineage, and observability, and partner with data engineers and subject matter experts (SMEs) to define data contracts and feature pipelines
You will modernize legacy case selection capabilities by decomposing them into scalable services and operationalizing rules and model-driven scoring, prioritization, routing, and human-in-the-loop review
You will build and operate production-grade ML pipelines with strong MLOps practices, including versioning, CI/CD, monitoring, drift detection, explainability, and fairness, and integrate with shared enterprise services using API-first and event-driven patterns
You will also harden the platform to meet security and compliance requirements, including ATO, produce architecture and operational documentation, and collaborate closely with product, fraud, and case management teams in an Agile delivery environment

Qualification

ML model deploymentMLOps practicesPythonDatabricksAPI-first integrationData quality improvementAgile deliveryResponsible AI practicesArchitecture documentationAWS certification

Required

Experience building, deploying, and operating production ML models such as supervised, unsupervised, and anomaly detection, including techniques for imbalanced datasets
Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining
Experience with Python and ML frameworks such as scikit-learn, PyTorch, or TensorFlow, and data engineering platforms such as Palantir, Databricks, Spark, and SQL, including batch and streaming pipelines
Experience improving data quality, lineage, and observability in enterprise data environments
Experience operationalizing rules and model-driven scoring for prioritization, routing, or case selection
Experience with API-first and event-driven integration patterns, including secure service-to-service communication
Experience working in Agile delivery environments, collaborating with product owners, SMEs, and engineering teams
Knowledge of Responsible AI practices, including explainability, fairness, and bias assessment
Ability to design and document architecture artifacts, data contracts, and operational runbooks
Bachelor's degree and 2+ years of experience with DevOps, software, or data engineering, or 5+ years of experience with DevOps, software, or data engineering in lieu of a degree

Preferred

Experience with fraud detection, risk analytics, or case selection in government, tax, or financial domains
Experience with Amazon Bedrock and integrating custom AI models into enterprise workflows
Experience deploying ML solutions in AWS GovCloud or other regulated cloud environments
Experience with federal ATO processes, continuous compliance, and operating systems under FISMA controls
Experience in enterprise modernization programs such as cloud migration, microservices, API strategy, and DevSecOps
Knowledge of graph-based analytics and advanced anomaly detection techniques
AWS Machine Learning Specialty, Security+, AI Engineer credentials, or similar Certification

Benefits

Health
Life
Disability
Financial
Retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care

Company

Jobs via Dice

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Funding

Current Stage
Early Stage
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