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Remote Machine Learning Engineer Jobs in Arizona

USAA

AI/ML Engineer II

Phoenix, AZ · On-site +1

$113K - $136K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Work with cross-functional team to contribute to machine learning projects throughout the machine ...

Waabi

Research Engineer

Phoenix, AZ · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Waabi

Research Engineer

Phoenix, AZ · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Phoenix Staff

Senior 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 ...

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All JobsRemote Machine Learning Engineer JobsRemote Machine Learning Engineer Jobs in Arizona

Remote Machine Learning Engineer information

See Arizona salary details

$29.4K

$120K

$180.3K

How much do remote machine learning engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for remote machine learning engineer in Arizona is $119,998.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires a strong track record, specialized certifications, and sometimes equity or bonuses as part of compensation packages.

Which 5 jobs will survive AI?

Remote Machine Learning Engineers are likely to continue to be in demand as AI advances, since they develop and maintain AI models and systems. Jobs that require complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled trades, are also expected to persist. Additionally, roles involving oversight, ethical considerations, and human interaction will remain essential despite automation.

What are the key skills and qualifications needed to thrive in the Remote Machine Learning Engineer position, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, and cloud platforms. Remote work arrangements depend on the employer's policies and project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.

Is ML full of coding?

A remote machine learning engineer role typically involves significant coding, especially in languages like Python or R, to develop algorithms and models. However, it also requires understanding data, model evaluation, and sometimes deploying solutions, making coding a core but not the sole component of the job.
What are the most commonly searched types of Machine Learning Engineer jobs in Arizona? The most popular types of Machine Learning Engineer jobs in Arizona are:
What are popular job titles related to Remote Machine Learning Engineer jobs in Arizona? For Remote Machine Learning Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Engineer jobs in Arizona look for? The top searched job categories for Remote Machine Learning Engineer jobs in Arizona are:
What cities in Arizona are hiring for Remote Machine Learning Engineer jobs? Cities in Arizona with the most Remote Machine Learning Engineer job openings:
Remote Machine Learning Engineer jobs near you

AI Engineer/ML Engineer - Senior Developers - AI Training - Tucson, US

Prolific Academic Ltd

Tucson, AZ • On-site, Remote

$80/hr

Full-time

Posted 2 days ago

Be an early applicant

Job description

AI & Machine Learning Engineer - AI TrainingAbout Prolific

Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world.

Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

The role

We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.

What you'll bring
  • Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
  • Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment.
  • Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
  • LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows.
  • Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
  • Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content.
What you'll be doing in the role
  • Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
  • Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
  • Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness.
  • Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down.
  • Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.
Key Technologies
  • Frameworks: expert proficiency in PyTorch or TensorFlow/Keras.
  • Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers.
  • Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
  • Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.
Why Prolific is a great platform to join as a Participant

Joining our Expert Network will give you the chance to influence the AI models of the future using your professional expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.
Click here to apply directly - https://app.prolific.com/register/participant/waitlist/?campaign_code=C14EMWJI
Links to more information on Prolific

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Privacy Statement

By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.