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Junior Machine Learning Jobs in Arizona (NOW HIRING)

Provide technical leadership to junior scientists, guiding the transition of R&D concepts into ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Provide technical leadership to junior scientists, guiding the transition of R&D concepts into ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

For data science/data analyst/data engineer/AI/machine learning positions preferred skills include an associate or bachelors degree or masters degree in computer science, computer engineering ...

Responsibilities - Design and implement advanced AI and machine learning solutions - Analyze intricate challenges and provide actionable insights - Mentor and guide junior team members in their ...

Senior AI Engineer - SFL Scientific

Tempe, AZ · On-site

$100K - $137K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

... Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation. - Publish high-impact research at top-tier conferences in machine learning or robotics.

... Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation. - Publish high-impact research at top-tier conferences in machine learning or robotics.

Snowflake Architect

Scottsdale, AZ · On-site

$64.25 - $82.50/hr

Provide technical guidance and mentorship to junior data engineers, ensuring best practices are ... Machine Learning: * Strong experience creating and tuning machine learning models in Azure and ...

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Junior Machine Learning information

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may require multiple years of experience and relevant certifications.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of specialized experience and a strong track record of impactful projects.

Can I get an AI job with no experience?

Entry-level machine learning roles, such as Junior Machine Learning positions, often require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is beneficial, candidates can improve their chances by completing relevant online courses, building projects, and gaining familiarity with tools like Python and TensorFlow.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and machine learning engineers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
What are the most commonly searched types of Machine Learning jobs in Arizona? The most popular types of Machine Learning jobs in Arizona are:
Infographic showing various Junior Machine Learning job openings in Arizona as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.
Junior Machine Learning Engineer-remote/AI/Data scientist

Junior Machine Learning Engineer-remote/AI/Data scientist

SynergisticIT

Phoenix, AZ • On-site

Other

Posted 25 days ago


Job description

Turn a Tech Layoff or a Career Gap Into a Reset for a Better Career or Laid Off in Tech? Rebuild Momentum With a Placement Process or Returning to Tech After a Break? Worried About a Gap? A layoff or a Career Gap can shake your confidence—even if you did nothing wrong. Downsizing, reorganizations, and budget cuts are business decisions, not personal failures. The tech industry still needs skilled developers — you just need the right platform to re-enter. A career gap doesn’t disqualify you — outdated skills do. But the job market can still feel brutal: you apply daily, watch automated rejections roll in, and wonder why your experience isn’t translating into interviews. The truth is that hiring has shifted. Employers want candidates who match current stacks, show recent hands-on proof, and interview strongly. If you’ve been out for 3–6+ months, that gap can become an extra filter—unless you deliberately rebuild momentum. We’re actively engaging candidates for full-time opportunities aligned to client needs: software programming, Java full stack development, Java/Python roles, DevOps engineering, and data roles spanning analytics, engineering, science, and ML/AI. Our primary focus remains Java/Full Stack/DevOps and Data/Engineering/Analytics/ML. SynergisticIT since 2010 has helped candidates land full-time roles at major organizations (examples often listed include Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, JPMC, Citi, Bank of America, Wayfair, and others), with offers in the $95k–$154k range depending on role and stack. Why laid-off candidates often struggle (even with experience) After a layoff, two things happen: Your skills may be solid, but your keywords and tools may be slightly behind the market. Your interview performance may drop because stress makes you second-guess. Also, employers increasingly expect hybrid capability: not just “I coded,” but “I can build + deploy + collaborate + document + explain.” That’s especially true for Java full stack, DevOps, data engineering, and ML/AI. What roles are commonly in demand right now Laid-off candidates often do best targeting roles that map to consistent enterprise demand. The main lanes include: Entry-level to mid-level software engineering roles (especially backend/full stack) Java full stack roles (enterprise stability) Java/Python developer roles (flexibility across teams) DevOps/Cloud roles (automation, pipelines, reliability) Data roles (analytics → engineering → ML/AI) why placement support matters rebuild a job-ready portfolio fast adjust your resume and LinkedIn for ATS practice interviews under real conditions get scheduled interviews through structured outreach A layoff recovery plan that actually works A smart recovery plan is not “apply more.” It’s: Re-stack: align skills to today’s demand (Java/full stack/devops or data/ML). Rebuild proof: projects that look like work, not homework. Rehearse interviews: DSA, system design, SQL, behavioral storytelling. Re-enter pipelines: structured outreach that leads to scheduled interviews. If you follow that with consistent coaching and iteration, your layoff becomes a pivot point—not a pause. If you’re ready to stop refreshing job boards and start rebuilding momentum with support, begin here: If you want to explore here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Discover JOPP: Job Placement Program Contact form:https://www.synergisticit.com/contact-us/ Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? Layoff reality: It can happen to anyone. Career recovery is a strategy problem, not a worth problem. In tech, it’s not only what you know—it’s how you position it and who guides you that determines how quickly you return stronger. Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don’t want to be contacted please don’t submit your resume.