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Afternoon Mechanical Engineering Machine Learning Jobs in Rutland, VT

Machinist (Band VII)

Rutland, 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.

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.

Ensure all machines and systems are primed for packaging to fulfill the daily and weekly ... Continuous Learning : Pursue ongoing education to deepen understanding of Warehouse processes and ...

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

Warehouse Operator

Florence, VT · On-site

$17 - $20.75/hr

Ensure all machines and systems are primed for packaging to fulfill the daily and weekly ... Continuous Learning : Pursue ongoing education to deepen understanding of Warehouse processes and ...

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Showing results 1-20

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 Aug 25, 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.

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.

What are the key skills and qualifications needed to thrive as an afternoon mechanical engineering machine learning professional?

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.

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.

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.

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 and models for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required.

Machine Learning Engineer (PhD Intern)

Rutland, VT • On-site


Instacart
Technology, Communication and Media • 10K+ employees

6.7

Company rating: 6.7 out of 10

Based on 32 frontline employees who took The Breakroom Quiz

42nd of 64 rated delivery companies

People enjoy working here

Recommended by students

Recommended by parents


Other

Re-posted 5 days ago


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.

Overview

Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.

We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.

About the Team:

This is a general posting for multiple intern roles open across our various ML teams. You can find a blurb on each team below:

Economics Team: The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.

Search & Discovery ML: The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search technology at Instacart. They collaborate on building models that enhance relevance of all shopping surfaces, ranking, and personalization, delivering highly relevant results to users across the Instacart ecosystem. As part of the Search and Discovery ML team, you'll work on one of the most critical aspects of the business, helping customers connect with the right products. We are passionate about solving large-scale search challenges and creating innovative solutions that elevate the customer experience. (Recent publications 1, 2, 3, 4, 5).

Content AI Team: The Content AI team at Instacart works alongside world-class engineers, data scientists, and product managers to advance generative AI, recommendations, and catalog intelligence in grocery ecommerce. We build cutting-edge AI models that power real-time recommendations, feed ranking, and automated content generation, ensuring high-quality and engaging customer experiences. Beyond recommendations, we leverage generative AI and LLMs to enhance and enrich Instacart’s catalog, driving AI-powered product understanding and content creation at scale. As part of Content AI, you'll work on high-impact AI solutions, applying LLMs, agentic systems, and computer vision to tackle complex challenges. We are passionate about pushing the boundaries of generative AI to shape the future of ecommerce. If you're excited about building state-of-the-art AI systems, we’d love to have you on board!

Past internship contributions include:

Tensor-based complementary recommendations, published at IEEE Big Data 2021 (Paper) Enhancing sequence-based recommendations for long-tail products (Blog)

About the Job

Based on your passion and background, you may choose to work in a few different areas:

  • Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
  • Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
  • Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
  • Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
  • Fraud detection and prevention - Using cost sensitive learning to reduce loss.
  • Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
  • Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.

About You

Minimum Qualifications:

  • Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
  • Strong programming (Python, C++) and algorithmic skills.
  • Good communication skills. Curious, willing to learn, self-motivated, hands-on.

Preferred Qualifications:

  • Ph.D. student at a top tier university in the United States
  • Prior internship/work experience in the machine learning space

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.


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


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

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