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Remote Machine Learning Jobs in Reno, NV (NOW HIRING)

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Remote Machine Learning information

See Reno, NV salary details

$25.4K

$42.5K

$87.7K

How much do remote machine learning jobs pay per year?

As of Jun 19, 2026, the average yearly pay for remote machine learning in Reno, NV is $42,459.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,400.00 and $45,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

Can I work remotely as a machine learning engineer?

Yes, many machine learning engineer roles are available for remote work, especially in companies that support flexible or distributed teams. Remote positions often require strong skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch, along with good communication skills. However, some roles may require on-site presence for collaboration or access to specialized hardware.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Which 5 jobs will survive AI?

Remote machine learning roles such as data scientists, AI researchers, machine learning engineers, AI product managers, and AI ethics specialists are expected to persist as AI advances. These jobs require specialized skills in programming, statistical analysis, and domain expertise that are difficult to fully automate. Continuous learning and proficiency in tools like Python, TensorFlow, or PyTorch are essential for these roles.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in competitive markets.

Are ML jobs in demand?

Machine Learning (ML) jobs are in high demand across various industries such as technology, finance, healthcare, and retail. The growth is driven by increasing adoption of AI solutions, data-driven decision making, and the need for expertise in programming, data analysis, and model deployment, making ML a promising career path.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are popular job titles related to Remote Machine Learning jobs in Reno, NV? For Remote Machine Learning jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Reno, NV look for? The top searched job categories for Remote Machine Learning jobs in Reno, NV are:
What cities near Reno, NV are hiring for Remote Machine Learning jobs? Cities near Reno, NV with the most Remote Machine Learning job openings:
Minerals Project Studies Lead - Senior Level (Hybrid/Remote)

Minerals Project Studies Lead - Senior Level (Hybrid/Remote)

Barr

Reno, NV โ€ข On-site, Remote

$121K - $164K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago


Job description

The role - what you'll do

Barr is seeking a senior minerals project studies lead to join our engineering and design team. In this hybrid role, you will lead and support multidisciplinary teams preparing and delivering scoping studies, preliminary economic analyses (PEA), pre-feasibility studies (PFS), and feasibility studies (FS) for Barr's minerals industry clients.

This role is responsible for managing the full scope of technical studies, ensuring work is completed safely, on schedule, and within budget, while integrating technical, permitting, and financial analyses to maximize project value. The studies lead will help ensure planning, preparation, and delivery are consistent and meet varying client needs. You will have the opportunity to successfully steer complex studies through our clients' stage-gate processes, developing and applying robust study management techniques, while leading a multidisciplinary team across multiple offices.

Your impact - key responsibilities

  • Technical expertise: ensure alignment of resources based on level of study.

  • Project management: manage a multidisciplinary team of professionals, manage project-level scope, schedule, and budget; conduct effective change management.

  • Professional responsibility: serve as the Qualified Person (QP) or Competent Person (CP) on relevant sections of studies published under the standards of Canadian National Instrument 43-101, United States SEC S-K 1300, and Australasian JORC.

  • Field support: project site reviews as required based on level of study.

  • Administrative: conduct business development, project management and scheduling, budget estimation, and workload estimation.

  • Mentorship: provide support through training and mentorship for other mining team members to develop their technical and study management skills.

About the opportunity

  • Hybrid or Remote:A hybrid or remote work arrangement may be considered for this position. A hybrid work arrangement refers to splitting time worked between a Barr office and a home office; a remote arrangement refers working primarily from a home office. This position can be based out of any of Barr's offices. Remote arrangements will be considered based on candidate qualifications, local regulations, and Barr's needs.

  • Travel expectation: up to 15 percent domestic or international fieldwork, depending on project needs

  • Work environment: ability to work in locations that have rough terrain typical of exploration areas and construction sites with limited accessibility, moving machinery, and other conditions typical of minerals industry facilities.

About you - required core competencies

  • Education: bachelor's degree in mining engineering, metallurgy, geology, or a related minerals industry discipline.

  • Experience: minimum of 10 years of relevant study experience.

    • Solid understanding of technical reporting standards (SK-1300, NI 43-101, and JORC).

    • Solid understanding of study project execution including project development phases (PEA, PFS, FS).

    • Demonstrated leadership skills in project management and/or project development.

    • Demonstrated project organization and management skills.

    • Experience with cost and financial modeling and CAPEX/OPEX estimation.

    • Experience working at mining and/or mineral processing operations is preferred.

    • Relevant experience with EPC/EPCM, mining construction, or successful studies completion is preferred.

    • Business development experience (such as lead finding for new projects) is preferred.

  • Licenses/certifications: Professional Engineer (PE or P.Eng.), Registered Member (SME or MMSA), or similar registration to support role as Qualified Person (QP) or Competent Person (CP)

  • Software: proficiency in Excel and MS Project (or similar scheduling program). Basic understanding of Microsoft Office Suite. Familiarity with CAD drawing reviews (such as Adobe or Bluebeam). Familiarity with various mine planning/modeling software packages.

  • Driver's license: possession of a current, valid driver's license and acceptable driving record.

  • Must be legally authorized to work in the United States without the need for sponsorship by Barr, now or in the future.

Compensation: anticipated range of $121,888-$164,112 annually. Compensation will vary based on relevant experience, education, skill level, and other compensable factors. Employees in this position may also be eligible for a discretionary cash bonus based on team and individual performance. This position is classified as exempt (salaried) under the Fair Labor Standards Act.

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Benefits - what we offer

We are committed to providing an employee experience that attracts and retains top talent. That's why we offer a competitive package of employee benefits - including some unique offerings not found at other companies. At Barr, we also believe that learning doesn't stop when you get your degree, which is why we provide coaching, mentoring, and support for ongoing educational opportunities to foster professional development at every stage of your career.

  • Competitive, affordable insurance plans: Medical, dental, vision, life, disability, accidental death insurance, and flexible spending accounts for medical and dependent care

  • Retirement benefits: 401(k) retirement savings plan with company contribution and an Employee Stock Ownership Plan (ESOP) with company contribution in Barr stock

  • Profit distribution: Barr has a "no retained earnings" model and distributes all profit to our employees through our annual bonus distribution plan, ESOP, and dividends to shareholders

  • Professional development benefits: Annual time and expense allowances, mentorship program, and many internal training opportunities

  • Work/life balance: Paid time off, holidays, overtime for non-exempt/hourly staff, and compensatory time for exempt/salaried staff (time off or pay for extra time worked), paid family leave

  • Wellness focus: Ergonomic analysis and equipment, Personal Protective Equipment allowance, wellbeing-focused educational opportunities

Please note that benefits eligibility is determined and may change based on part-time, reduced-time, or full-time status.

About us - why choose Barr

At Barr, you'll join a community of engineers, scientists, and professionals who will help you achieve your ambitions and build a meaningful, rewarding career. You'll serve as a trusted advisor to clients who value Barr's tailored solutions and commitment to exceptional service.

As part of our employee-owned firm, you'll contribute to a culture of commitment and camaraderie where staff can thrive as professionals. We value diverse perspectives and experiences and believe an inclusive workplace is critical to our success.

To learn more about Barr's culture and values, visit: https://www.barr.com/Careers/Our-culture

Open positions at Barr Engineering Co. do not have application deadlines. Barr Engineering Co. is an equal opportunity employer, and all applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.