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

DataAnnotation

SDLC Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

SDLC Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

Software Test Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Sparks, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

Automated QA Engineer - AI Trainer

Reno, NV · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Reno, NV

Machine Learning Engineer information

See Reno, NV salary details

$31.4K

$128.4K

$192.9K

How much do machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for machine learning engineer in Reno, NV is $128,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $154,500.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Reno, NV? The most popular types of Machine Learning Engineer jobs in Reno, NV are:
What are popular job titles related to Machine Learning Engineer jobs in Reno, NV? For Machine Learning Engineer jobs in Reno, NV, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Reno, NV look for? The top searched job categories for Machine Learning Engineer jobs in Reno, NV are:
What cities near Reno, NV are hiring for Machine Learning Engineer jobs? Cities near Reno, NV with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Reno, NV as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $128,391 per year, or $61.7 per hour.
Mechanical Engineer - Battery Sorting, Energy Storage

Mechanical Engineer - Battery Sorting, Energy Storage

Redwood Materials

Mccarran, NV • On-site

Other

Posted 3 days ago

Job description

Mechanical Engineer - Battery Sorting, Energy Storage

Do you want to design and build the automated systems that make battery recycling possible at scale? Join the Battery Sorting team at Redwood Materials, where we are building a world-class, state-of-the-art, ML-enabled sorting platform that integrates conveyors, diverter mechanisms, computer vision, and operator-assist systems to classify and route thousands of end-of-life batteries per hour across diverse chemistries and form factors.

Our team partners closely with Controls, Software, and Production Engineering to solve tightly coupled electromechanical and AI-driven challenges as we scale the infrastructure driving the circular battery economy. By increasing the reach of recycled and sustainable materials, we are transforming the global battery supply chain.

As a Mechanical Engineer on the Sorting team, you'll work alongside a world-class, cross-functional group of engineers to design, fabricate, integrate, and sustain production sorting equipment. We're looking for hands-on problem solvers who are energized by rapid iteration, people who can move fluidly between CAD, the shop floor, and the production line to keep hardware performing.

If you're ready to make a tangible impact on the future of sustainable manufacturing, we want to hear from you.

Responsibilities:

  • Design, prototype, and implement mechanical assemblies for sorting line subsystems including infeed, outfeed, conveyors, diverters, and guarding
  • Collaborate with production engineering to troubleshoot and improve existing sorting equipment and processes to maximize throughput and uptime
  • Apply engineering fundamentals (structural sizing, mechanism design, tolerance analysis) to deliver robust hardware solutions
  • Create detailed models and engineering drawings in SolidWorks for custom fixtures, brackets, enclosures, and conveyor components
  • Support machine activation alongside the controls engineering team; participate in development testing and validation runs with production engineering
  • Assist with integration of sensors, cameras, and actuators into mechanical assemblies, ensuring hardware interfaces support the ML-based classification and computer vision pipeline
  • Contribute novel mechanical concepts and designs with the potential to generate intellectual property and patents

Basic Qualifications:

  • Bachelor's degree in Mechanical Engineering or a related engineering discipline
  • Experience using a CAD software design package (e.g., SolidWorks, NX, CATIA, or ProE)
  • Internship, co-op, or up to 2 years of professional experience in mechanical design (new graduates welcome)

Preferred Skills and Experience:

  • Hands-on fabrication or prototyping experience (3D printing, sheet metal, welded structures, manual machining)
  • Exposure to conveyor systems, material handling equipment, or automated sorting/packaging machinery
  • Familiarity with sensor and actuator integration (encoders, servos, pneumatics, proximity sensors, cameras)
  • Interest in or exposure to machine learning, computer vision, or AI-enabled manufacturing systems
  • Understanding and application of GD&T
  • Experience working in or adjacent to a production or manufacturing environment
  • Comfort with engineering hand calculations and basic FEA
  • Ability to prioritize and execute tasks in a fast-paced, dynamic environment
  • Strong collaboration skills, including daily interactions with engineers, maintenance technicians, suppliers, and leadership

Additional Requirements

  • Work schedule may vary depending on site operational needs, and flexibility is required
  • Ability to work in challenging working conditions which may include exposure to noise, dust, chemicals, and temperature extremes, while protected by PPE, for extended periods of time
  • Must be able to lift and carry up to 50 lbs. as needed

Apply