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Internship Scale Master Jobs (NOW HIRING)

Avride

Research Engineer Internship

Austin, TX · On-site

Data-Driven Experimentation: run experiments on large-scale scenario pools, comparing ML agents ... Currently pursuing a Bachelor's, Master's, or PhD (highly preferred) in Computer Science, Robotics ...

Avride

Research Engineer Internship

Austin, TX · On-site

Data-Driven Experimentation: run experiments on large-scale scenario pools, comparing ML agents ... Currently pursuing a Bachelor's, Master's, or PhD (highly preferred) in Computer Science, Robotics ...

Einride

Einride Summer Internship 2026 - US

Austin, TX · On-site

$14.75 - $20/hr

... and scaling fast. We sit at the intersection of customer success, sales, logistics, and data ... At least 1 semester remaining until graduating from your bachelor or master studies. * Fluency in ...

TEK Systems

Orlando SDR Internship

Orlando, FL · On-site

$14 - $18.75/hr

... scale, full-stack capabilities and speed ... We're strategic thinkers, hands-on collaborators, helping customers capitalize on change and master ...

WOWK-TV

Events Intern Summer Internship

Washington, DC

$18.40/hr

... scale conferences. Key Responsibilities: - Assist in the planning and logistics of events ... Qualifications: - Current enrollment in a Bachelor's or Master's program, preferably in Journalism ...

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How much do internship scale master jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for internship scale master in the United States is $16.65, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $18.51 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Scale Master, and why are they important?

To thrive as an Internship Scale Master, you generally need strong organizational skills, attention to detail, and a background in logistics or transportation management, often supported by a relevant degree or coursework. Familiarity with weighbridge software, inventory management systems, and basic data entry tools is typically required. Excellent communication, problem-solving abilities, and reliability are standout soft skills for this role. These skills ensure accurate weight recording, efficient operations, and compliance with regulatory standards in transportation and logistics environments.

What types of projects and responsibilities can an Internship Scale Master expect during their internship?

As an Internship Scale Master, you can expect to participate in projects that focus on optimizing and streamlining operational processes within the company, often working alongside experienced operations and project management teams. Your daily tasks may include analyzing workflow data, assisting in implementing scalable solutions, and collaborating with cross-functional teams to identify areas for improvement. Interns in this role often gain hands-on experience with project management tools and methodologies, preparing them for more advanced roles in operations or process management.

What is an Internship Scale Master?

An Internship Scale Master typically refers to someone responsible for overseeing or managing the weighing process at facilities such as warehouses, recycling centers, or manufacturing plants during an internship. Their main duties include operating scale equipment, recording weight data, and ensuring accurate measurements for materials coming in or going out. This role provides interns with hands-on experience in logistics, inventory management, and operations. The position may also involve interacting with truck drivers, verifying documentation, and learning safety protocols relevant to the weighing process.

What is the difference between Internship Scale Master vs Project Coordinator?

AspectInternship Scale MasterProject Coordinator
Required CredentialsTypically pursuing or holding a degree in business, management, or related fieldsOften holds a degree in business, management, or related fields
Work EnvironmentInternship setting, often in corporate or organizational environmentsOffice-based, coordinating projects across teams
Employer & Industry UsageUsed in industries like corporate, non-profit, and government for managing internship programsCommon in various industries for overseeing project execution

The Internship Scale Master primarily focuses on managing and scaling internship programs, often during an internship or entry-level role. In contrast, a Project Coordinator handles specific projects, ensuring tasks are completed on time. While both roles require organizational skills and industry knowledge, the Internship Scale Master is more specialized in internship program management, whereas the Project Coordinator has a broader project oversight role.

What cities are hiring for Internship Scale Master jobs? Cities with the most Internship Scale Master job openings:
What are the most commonly searched types of Scale Master jobs? The most popular types of Scale Master jobs are:
What states have the most Internship Scale Master jobs? States with the most job openings for Internship Scale Master jobs include:
Internship Scale Master jobs near you

Research Engineer Internship

Avride

Austin, TX • On-site

Internship

Posted 12 days ago

Job description

About Avride
Avride is a US-based developer of autonomous vehicles and delivery robots. We develop and operate both autonomous cars and delivery robots that share technologies and mutually benefit from each other's advancements-a unique approach in the industry.
About the Internship
At Avride, Research Engineer Interns operate at the intersection of cutting-edge academic research and real-world engineering. You will use our massive datasets of real driving logs to train models and develop algorithms.
During this internship, you will be embedded in the ML Prediction and Planning team, which is responsible for building machine learning models that enable autonomous vehicles to understand their environment and make safe, efficient driving decisions on real roads. The team focuses on predicting the behavior of surrounding agents and generating trajectories that the vehicle can follow in complex, dynamic scenarios.
You will be paired with a dedicated senior researcher and work on problems directly impacting real-world driving performance. This program is designed to give you a deep understanding of how to take a theoretical concept from a research paper, prototype it, and evaluate its performance in a complex, safety-critical system.
What You'll Do
We are currently offering two different internships within our ML Prediction and Planning team for the Summer of 2026.
Autonomous Vehicles
  • Applied Research Project: Take ownership of a research project focused on exploring how model ensembling strategies influence the gap between open-loop (training) and closed-loop (simulation) performance. You will review relevant literature, formulate hypotheses, and prototype solutions using Python and ML frameworks (like PyTorch).
  • Design Ensembling Strategies: Implement and evaluate multiple ensembling approaches, including blending models trained with different random seeds, combining checkpoints from different training stages, and applying weighted averaging or learned blending of model outputs.
  • Run Controlled Experiments: Systematically compare single-model vs ensemble performance and seed diversity vs checkpoint diversity, and measure their impact on open-loop metrics (training/validation loss, accuracy) and closed-loop metrics (simulation performance, safety, stability).
  • Analyze Metric Alignment: Investigate the correlation (or lack thereof) between open-loop and closed-loop improvements, identify cases where ensembling improves one metric but degrades the other, and formulate hypotheses explaining the observed behavior.

Simulation
  • Applied Research Project: You will work on evaluating and improving the behavior of ML-driven traffic agents in our autonomous driving simulator. Our prediction model generates multiple trajectory candidates for each simulated agent at every step. Your job is to design evaluation functions that select trajectories with desired properties - from realistic to adversarial - and build quantitative metrics to measure how agent behavior changes. Today we assess realism visually; you will replace that with data-driven evaluation that becomes the standard tool for measuring every future improvement to our agent simulation. You'll work with real driving data, run experiments on large scenario pools, and produce results that directly influence the team's roadmap for agent simulation.
  • Design and implement algorithms: work alongside your mentor to design, test, and iterate algorithms that select agent trajectories optimizing for different objectives: aggressiveness, interaction density, route fidelity.
  • Build evaluation metrics: for comparing agent behavior strategies: interaction intensity (time-to-collision, proximity), kinematics plausibility (acceleration, jerk), and distributional similarity to real traffic.
  • Data-Driven Experimentation: run experiments on large-scale scenario pools, comparing ML agents agains baseline approaches and measuring the impact of different strategies.
  • Work with production codebase: the prediction models you'll experiment with are the same ones deployed in our autonomous vehicles. Your work is a part of a C++ simulation pipeline running large-scale scenario evaluation.
  • Knowledge Sharing: Conclude your internship by presenting your methodology, experimental results, and data-driven recommendations on where trajectory ranking is sufficient and where model-level changes are required.
What You'll Need
  • Education: Currently pursuing a Bachelor's, Master's, or PhD (highly preferred) in Computer Science, Robotics, Machine Learning, Applied Mathematics, or a related field with an expected graduation date between Winter 2026 and Spring 2027.
  • Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling.
  • Programming Skills: Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow). Basic familiarity or willingness to learn C++.
  • Research Acumen: Ability to read, understand, and implement algorithms from academic research papers. A strong analytical mindset for designing experiments and interpreting data.
  • Eagerness to Learn: Highly collaborative, open to feedback, and excited to tackle unsolved problems in the autonomous driving space.
What You'll Get
  • 1:1 Mentorship: Direct guidance from leading researchers and engineers in the autonomous vehicle industry to help you navigate technical roadblocks and grow your career.
  • Massive Compute & Data: Access to state-of-the-art driving data to fuel your experiments.
  • Networking & Culture: Invitations to tech talks, paper reading groups, intern social events, and cross-team collaborations.

Please note that this is an in-person internship based at our office in Austin, Texas. We are prioritizing candidates who currently reside within commuting distance of Austin. We do not provide relocation assistance, travel reimbursement, or housing stipends for this position.
Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.

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