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Afternoon Mechanical Engineering Machine Learning Jobs in Rutland, VT

Bespoke Labs

Machine Learning Engineer

Rutland, VT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

CARRIS REELS GROUP

Machinist (Band VII)

Rutland, VT

$22.65 - $26.03/hr

Machine Guarding: * Fabricate, inspect, install, and maintain machine guards, barriers, and safety ... Recommend engineering controls and design improvements to reduce exposure to mechanical hazards.

New

Carris Reels, Inc.

Machinist (Band VII)

VT · On-site

$22.65 - $26.03/hr

Machine Guarding: * Fabricate, inspect, install, and maintain machine guards, barriers, and safety ... Recommend engineering controls and design improvements to reduce exposure to mechanical hazards.

New

Manpower

Maintenance Technician

Rutland, VT

You will be responsible for the overall performance of a variety of machines within the facility ... Proficient with PLCs, operation and programming (preferred) * technical training in mechanical and ...

New

Jeld-Wen Inc.

Maintenance

Ludlow, VT

... cause of machine issuesPerform mechanic skills including, but not limited to, mechanical ... programming and HMI PanelsCritical thinking and exceptional problem-solving skillsProactive ...

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Afternoon Mechanical Engineering Machine Learning information

See Rutland, VT salary details

$46.6K

$105.4K

$170.5K

How much do afternoon mechanical engineering machine learning jobs pay per year?

As of Jul 16, 2026, the average yearly pay for afternoon mechanical engineering machine learning in Rutland, VT is $105,379.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $129,600.00 per year, depending on experience, location, and employer.

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding of data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required for such positions.

What are the key skills and qualifications needed to thrive as an Afternoon Mechanical Engineering Machine Learning professional, and why are they important?

To excel in this role, you need a solid background in mechanical engineering principles, mathematics, and machine learning concepts, usually supported by a relevant engineering degree. Familiarity with technical tools such as Python, MATLAB, CAD software, and machine learning frameworks (like TensorFlow or scikit-learn) is typically required. Strong analytical thinking, problem-solving, and effective teamwork are valuable soft skills for integrating machine learning with mechanical systems. These competencies are crucial for developing innovative solutions and optimizing engineering processes with data-driven approaches.

What is the difference between Afternoon Mechanical Engineering Machine Learning vs Afternoon Mechanical Engineering Data Analysis?

AspectAfternoon Mechanical Engineering Machine LearningAfternoon Mechanical Engineering Data Analysis
Required CredentialsBachelor's or Master's in Mechanical Engineering, proficiency in machine learning toolsBachelor's or Master's in Mechanical Engineering, strong data analysis skills
Work EnvironmentResearch labs, tech companies, manufacturing firmsDesign firms, manufacturing plants, research institutions
Employer & Industry UsageTech-driven engineering sectors applying AI/MLTraditional engineering sectors focusing on data interpretation
Search & Comparison IntentUnderstanding roles involving AI/ML in mechanical engineeringComparing data analysis tasks within mechanical engineering

Afternoon Mechanical Engineering Machine Learning focuses on applying AI and machine learning techniques to mechanical engineering problems, often requiring programming and data modeling skills. In contrast, Afternoon Mechanical Engineering Data Analysis emphasizes interpreting and visualizing data to inform engineering decisions. Both roles share foundational engineering knowledge but differ in their technical focus and application areas.

Will MLE be replaced by AI?

In the context of an Afternoon Mechanical Engineering Machine Learning role, MLE (Machine Learning Engineer) involves designing and deploying models that often complement AI systems. While AI automation can handle certain tasks, MLE professionals are essential for developing, optimizing, and maintaining machine learning solutions, making complete replacement unlikely in the near term. Skills in programming, data analysis, and understanding of algorithms remain critical for MLE roles.

What engineer makes $500,000 a year?

Senior mechanical engineers with extensive experience, specialized skills in machine learning, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large corporations. Achieving this level often requires advanced degrees, certifications, and a strong track record of project success and innovation.

How do mechanical engineers specializing in machine learning typically collaborate with other departments during afternoon shifts?

Mechanical engineers working in machine learning often collaborate closely with data scientists, software developers, and production teams, especially during afternoon shifts when testing and implementation often ramp up. They may participate in cross-functional meetings to align on project goals, troubleshoot issues with live data, and refine machine learning models based on feedback from manufacturing or operations staff. This collaborative environment helps ensure that algorithms are practical, efficient, and aligned with real-world applications. Effective communication and adaptability are key, as priorities can shift rapidly based on production needs.

Can you make $200,000 a year as a mechanical engineer?

Achieving a $200,000 annual salary as a mechanical engineer is possible but typically requires extensive experience, advanced skills in areas like machine learning or automation, and often positions in management or specialized industries such as aerospace or energy. Salaries vary based on location, company size, and individual expertise, with top earners often holding senior or lead roles and possessing professional certifications.

What is an Afternoon Mechanical Engineering Machine Learning job?

An Afternoon Mechanical Engineering Machine Learning job typically refers to a position where professionals apply machine learning techniques to solve problems in mechanical engineering, with working hours scheduled in the afternoon. These roles often involve analyzing engineering data, developing predictive models, and optimizing mechanical systems using advanced algorithms. The work may include tasks such as fault detection, predictive maintenance, or process optimization, leveraging both engineering expertise and machine learning skills. Employees in such positions usually have backgrounds in both mechanical engineering and computer science or data analytics.
Afternoon Mechanical Engineering Machine Learning jobs near you
Machine Learning Engineer II, Logistics AI

Machine Learning Engineer II, Logistics AI

Instacart

Rutland, VT • On-site

Full-time

Re-posted 24 days ago

Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

29th of 63 rated delivery companies

Job description

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

About the Role:

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart's marketplace systems. You will use machine learning to devise and refine solutions in crucial areas such as routing optimization, pricing, dispatch, and mapping. You will actively contribute to initiatives, assisting in all stages from the initial concept, through prototyping and experimentation, to final implementation.

About the Team:

The Logistics AI group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML/AI applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.

About You:

Minimum Qualifications:

  • Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience 
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels

Preferred Qualifications:

  • Have 1-2 years of industry experience using machine learning to solve real-world problems with large datasets
  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For US based candidates, the base pay ranges for a successful candidate are listed below.

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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