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Ai Ml Analyst Jobs (NOW HIRING)

DecisionPoint | Cortek

AI/ML Architect

$65.25 - $84/hr

This role develops predictive analytics solutions, anomaly detection models for IT and ... The AI/ML Architect collaborates closely with data scientists, dashboard teams, engineering staff ...

Randstad Digital

AI / ML Data Analyst

Charlotte, NC · On-site

$40.70 - $50.70/hr

We are seeking a highly motivated Data Analyst with strong analytical skills and practical knowledge of Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics to transform data into ...

CloudBCLabs

AI/ML Architect

Plano, TX · On-site

$61.25 - $78.75/hr

Technical leadership with analytical, problem solving and communication skills * Familiarity with cloud AI/ML platform offerings, features * Understanding of AI services for speech, vision and text.

New

Tror AI for everyone

AI/ML Architect

Los Angeles, CA · On-site

$68.75 - $88.25/hr

AI/ML Architect with Databricks, Azure Location: Los Angeles CA or New York NY (Hybrid) Hire type ... This role requires working with large, multi-terabyte datasets, advanced analytics, and ...

Starfish

AI/ML Engineer

Redstone Arsenal, AL · On-site

Torch Technologies is seeking a highly analytical and mathematically minded Artificial Intelligence/Machine Learning (AI/ML) Engineer to join our AI/ML team. The candidate will support the Missile ...

Lululemon Athletica

AI/ML Scientist

Seattle, WA · On-site

$147 - $193/hr

The team leads the design and delivery of a trusted unified data foundation, advanced analytics ... Core responsibilities As an Applied AI/ML Scientist, you design, develop, test, and optimize AI/ML ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Required : • Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research ...

Aivra Health LLC

AI/ML Engineer

Dallas, TX · On-site

AI/ML Engineer Location: Dallas, TX, United States Job Type: Full-Time Experience: 0-3 years Work ... Analyze model performance and improve accuracy, scalability, and efficiency. Required Skills

Interon IT Solutions

AI/ML Engineer

Reston, VA · On-site

AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate ... time analytics, and model inference. * Architect and operationalize RAG pipelines , embeddings ...

Starr

AI/ML Engineer

Manhattan, NY · On-site

The AI/ML Engineer will uncover meaningful data patterns and transform them into actionable ... D. preferred. • 2+ years of experience with advanced analytics techniques (e.g., decision tree ...

Socket.dev

AI/ML Engineer

San Francisco, CA · On-site

$110 - $150/hr

Ability to communicate analyses and model findings clearly, clarify requirements, and collaborate ... Chime's AI/ML Trust & Safety team is building models, insights, and decisioning systems that help ...

Virtusa Corporation

AI/ML Engineer

New York, NY · On-site

The ideal candidate will lead solution design, predictive analytics, and time-series modeling ... Key Responsibilities AI/ML & Generative AI Development Design and implement advanced ML models ...

Starr Insurance Companies

AI/ML Engineer

New York, NY · On-site +1

He/she will be passionate about learning and deploying leading technologies in the analytics space specific to the business needs to drive results and identify opportunities. As an AI/ML Engineer ...

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Ai Ml Analyst information

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How much do ai ml analyst jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for ai ml analyst in the United States is $35.97, according to ZipRecruiter salary data. Most workers in this role earn between $25.24 and $42.07 per hour, depending on experience, location, and employer.

What is the difference between Ai Ml Analyst vs Data Scientist?

AspectAi Ml AnalystData Scientist
Required CredentialsBachelor's in CS, Data Science, or related fields; certifications in AI/MLBachelor's or higher in CS, Statistics, or related; advanced certifications often preferred
Work EnvironmentData analysis, model deployment, collaboration with engineering teamsData exploration, model building, statistical analysis, storytelling with data
Industry UsageTech, finance, healthcare, retailTech, finance, healthcare, research institutions

While both roles involve working with data and machine learning, Ai Ml Analysts focus more on applying models to solve specific problems and deploying solutions, whereas Data Scientists often engage in deeper data exploration, developing new models, and deriving insights. The roles overlap but differ in scope and depth of analysis.

What is an AI ML analyst?

An AI ML analyst is a professional who develops, implements, and evaluates artificial intelligence and machine learning models to solve business problems. They often work with data analysis, programming languages like Python or R, and machine learning frameworks such as TensorFlow or scikit-learn to create predictive algorithms and insights.
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Ai Ml Analyst jobs near you
Infographic showing various Ai Ml Analyst job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $74,823 per year, or $36 per hour.

AI/ML & Analytics Platform Engineer

MDAEdge

Plainsboro, NJ • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
MDAEdge is a company specializing in AI and analytics solutions, seeking an AI/ML & Analytics Platform Engineer to contribute to their platform development. The role involves building capabilities for scalable AI/ML workflows and collaborating with cross-functional teams to enhance platform performance and deployment efficiency.
Responsibilities:
• Contribute to building AI/ML & Analytics platform, services, and tools across dev, test, and prod environments to accelerate model training, inference, and deployment.
• Build capabilities for batch and real-time workflows at scale with flexible deployment strategies for use cases like low-latency predictions and offline inference.
• Improve platform performance, reduce manual intervention, scale compute, and increase deployment efficiency.
• Collaborate with cloud teams to ensure operational effectiveness, reliability, security, and efficiency.
• Provide technical guidance on monitoring systems like registries and alerting, plus governance frameworks for regulatory compliance.
• Work with cross-functional teams on AI/ML system architecture, deployment pipelines, and solution scaling.
• Champion self-service patterns, IaC, and GitOps for platform development.
Qualifications:
Required:
• Bachelor's or Master's in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or related field.
• Experience building scalable AI/ML & Analytics platforms for ML Researchers, Engineers, Data Scientists, and Analysts.
• Proficiency in Python, Spark, SQL, and ML frameworks like PyTorch or TensorFlow.
• Strong AWS knowledge, including AI/ML services like SageMaker.
• IaC tools such as Terraform, OpenTofu, CDK, or Pulumi, plus CI/CD pipelines.
• Containerization with Docker or Podman, and orchestration with Kubernetes or Rancher.
• VCS like GitHub or GitLab, CI/CD tools like GitHub Actions or Jenkins, and JIRA.
• Ops fundamentals including registries, observability, monitoring, performance analysis, and cost optimization.
• Hands-on problem-solving for technical and architectural challenges in scalable, secure platforms.
• Automation-first mindset with security consciousness and focus on developer experience.
• Strong communication to engage stakeholders effectively.
• Ability to work collaboratively in cross-functional, agile teams valuing individual development.
Preferred:
• Pharma/biotech domain experience.
• Strongly typed languages like C/C++, Java, Go, or Rust.
• Large-scale distributed systems like Ray, Dask, Spark, or HPC like Slurm.
• Data platforms like Databricks, Snowflake, or dbt with Delta, Iceberg, Hudi.
• Real-time streaming like Kafka or Spark Streaming.
• GitOps tools like ArgoCD or Crossplane.
• Multi-cloud (AWS, GCP, Azure).
• High-performance inference frameworks like ONNX Runtime, TensorRT, or Triton.
• Large-scale CPU/GPU infrastructure with CUDA knowledge.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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