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Remote Google Machine Learning Engineer Jobs in Arizona

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We're looking for a ... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ...

Insight

This is a remote work opportunity Insight at a Glance * 14,000+ engaged teammates globally * #20 on ... About the role As a Google Workspace Customer Engineer at Insight, your role demands close ...

Ascend Learning

Principal AI Engineer

Gilbert, AZ · On-site +1

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Advanced understanding and practical experience in machine learning and natural language processing ...

micro1 AI

LLM Alignment Specialist - Engineering

Mesa, AZ · Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Dutchbros

Lead Engineer, Data Platforms

Tempe, AZ · On-site +1

$111K - $133K/yr

... machine learning, and AI-driven workflows and will be responsible for designing and implementing ... Location Requirement: This position is eligible for remote work within any state Dutch Bros ...

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handsa'on experience in ... Analytics & Machine Learning * Build ML pipelines for risk stratification, cost/utilization ...

Motorola

Senior DevOps Engineer (US REMOTE)

Phoenix, AZ · Remote

$140K - $170K/yr

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

micro1 AI

Domain Expert - (STEM PhD)

Phoenix, AZ · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

micro1 AI

Domain Expert - (STEM PhD)

Mesa, AZ · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Remote Google Machine Learning Engineer information

What is a Remote Google Machine Learning Engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a Remote Google Machine Learning Engineer, and why are they important?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do Remote Google Machine Learning Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.
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Remote Google Machine Learning Engineer jobs near you
Senior AI Engineer / Data Scientist

Senior AI Engineer / Data Scientist

Koantek

Chandler, AZ • Remote

Contractor

Posted 15 days ago

Job description

Senior AI Engineer / Data Scientist (Consulting) Location: United States (Remote) Employment Type: Full-Time / Contract Experience Level: Senior About the Role: We are seeking an experienced, highly technical Senior AI Engineer / Data Scientist to join our customer-facing consulting team. This remote role requires a unique blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. You will design, deploy, and maintain production-grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base.

Key Responsibilities: * Technical Consulting: Lead end-to-end ML implementations directly with clients, translating business problems into robust technical solutions. * MLOps and Pipelines: Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability. * GenAI and NLP Deployment: Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings.

* Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark. * Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences. Required Qualifications: * 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory).

* 3+ years of experience in a customer-facing consulting or Solutions Architect role. * Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment). * Solid hands-on experience with containerization (Docker) and data pipeline orchestration.

* Proven track record of deploying Generative AI and NLP solutions for client applications. * Excellent verbal and written communication skills. Preferred Qualifications: * Hands-on experience with modern ML platform stacks, specifically Databricks MLOps Stacks.

* Deep knowledge of large-scale data processing and distributed machine learning techniques. * A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.

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