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Remote Language Learning App Jobs in Tecumseh, MI

Lovable Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

Deep knowledge of Lovable AI-powered application builder including natural language app creation, U ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100K - $132K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... learning and natural language processing * Experience leading technical workstreams within a ...

Systems Integration Developer

Ann Arbor, MI · On-site +1

$150K - $180K/yr

Ability to use natural language authoring, variable/condition logic, and event triggers in Copilot ... Familiarity with Azure services including Logic Apps, Azure AD, Data Factory, SQL, App Services ...

Remote Language Learning App information

See Tecumseh, MI salary details

$10.8K

$82.6K

$137.8K

How much do remote language learning app jobs pay per year?

As of Aug 10, 2026, the average yearly pay for remote language learning app in Tecumseh, MI is $82,566.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,900.00 and $136,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote language learning app developer?

To thrive as a Remote Language Learning App Developer, you need strong programming skills (such as in JavaScript, Swift, or Kotlin), experience with mobile app development, and a background in UI/UX design or educational technology. Familiarity with frameworks like React Native or Flutter, cloud services, and agile development methodologies is typically required. Excellent problem-solving, communication, and collaboration skills help you work effectively with distributed teams and understand user needs. These skills ensure the creation of engaging, functional, and accessible apps that effectively support language learners worldwide.

What are some common challenges faced by remote language learning app instructors, and how can they be overcome?

Remote language learning app instructors often face challenges such as maintaining student engagement, adapting teaching methods to a virtual environment, and managing time zone differences with a global student base. To overcome these, instructors frequently use interactive tools, varied multimedia content, and personalized feedback to keep learners motivated. Additionally, clear communication and flexible scheduling help in building rapport and accommodating diverse learners. Collaboration with curriculum designers and tech support teams is essential to continually improve the learning experience.

What is the difference between Remote Language Learning App vs Language Tutor?

AspectRemote Language Learning AppLanguage Tutor
CredentialsTypically no formal credentials required, but certifications can enhance credibilityOften requires teaching certifications or language proficiency credentials
Work EnvironmentOnline platform, flexible hours, self-pacedUsually live sessions, scheduled meetings, can be remote or in-person
Employer & Industry UsageUsed by educational companies, language platforms, and self-employed tutorsEmployed by language schools, private clients, or freelance
Search & Comparison IntentLooking for scalable, automated language learning solutionsSeeking personalized, interactive language instruction

The main difference between a Remote Language Learning App and a Language Tutor lies in their delivery and interaction. Apps provide automated, self-guided learning experiences without live interaction, while language tutors offer personalized, real-time instruction. Both serve different learner needs, with apps being more flexible and scalable, and tutors providing tailored feedback and engagement.

What is a remote language learning app?

A remote language learning app is a digital platform or software that allows users to learn new languages from anywhere using an internet-connected device. These apps often include interactive lessons, quizzes, and practice exercises for reading, writing, listening, and speaking. Many remote language learning apps use features like speech recognition, spaced repetition, and gamification to make learning more engaging and effective. They are popular for their flexibility, convenience, and wide range of available languages.
What cities near Tecumseh, MI are hiring for Remote Language Learning App jobs? Cities near Tecumseh, MI with the most Remote Language Learning App job openings:

Senior, Machine Learning Engineer - End-to-End

Torc Robotics

Ann Arbor, MI • On-site, Remote

$119K - $158K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago


Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team:
As a Senior Machine Learning Engineer - End-to-End (E2E), you will develop and scale learning-based systems that connect multi-modal perception inputs to driving behavior, enabling safe, efficient, and human-like autonomy for real-world freight operations.
You'll work at the intersection of perception, prediction, and planning, contributing to unified learning pipelines that operate in closed-loop environments. This role focuses on owning meaningful portions of the E2E stack, improving model performance at scale, and driving iteration through data, experimentation, and cross-functional collaboration.
This is a hands-on engineering role focused on execution, iteration, and delivery.
What You'll Do
  • Own development and delivery of End-to-End ML models that map multi-modal sensor inputs (camera, LiDAR, radar, maps) to driving-relevant outputs (trajectories, cost functions, or intermediate representations)
  • Train and evaluate models using large-scale datasets from fleet logs, simulation, and synthetic data
  • Analyze model performance, identify failure modes, and drive data-driven improvements in robustness and generalization
  • Design and refine training pipelines, data workflows, and evaluation strategies to improve iteration speed and model quality
  • Contribute to model architecture decisions, including approaches such as imitation learning, reinforcement learning, transformers, and vision-language-action (VLA) models
  • Collaborate closely with Perception, Prediction, Planning, and Simulation teams to ensure alignment across the autonomy stack
  • Support integration of E2E models into simulation and on-vehicle systems for closed-loop validation
  • Improve tooling, experimentation workflows, and reproducibility across the team
  • Mentor junior engineers and contribute to team-level best practices and technical discussions

What You'll Need to Succeed
  • Bachelor's degree with 6+ years, Master's with 4+ years, or PhD with 0-2 years of experience in Machine Learning, Robotics, Computer Science, or a related field with a track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
  • Experience developing and deploying ML models for autonomous systems, robotics, or complex decision-making environments
  • Strong programming skills in Python and PyTorch, with ability to write production-quality ML code
  • Experience training and evaluating models using large-scale datasets and distributed compute environments
  • Solid understanding of ML architectures used in E2E systems, such as Transformers, BEV models, VLA/VLM approaches, or diffusion models
  • Proven ability to debug model behavior, analyze performance metrics, and drive iterative improvements
  • Experience contributing to or influencing model architecture and training strategies
  • Ability to work cross-functionally and integrate ML systems into larger autonomy pipelines

Bonus Points
  • Experience developing End-to-End or mid-to-end models for autonomous driving or robotics
  • Experience with vision-language models (VLMs) or vision-language-action (VLA) systems
  • Familiarity with closed-loop simulation and evaluation frameworks
  • Experience with reinforcement learning or imitation learning in real-world systems
  • Experience with distributed training frameworks (e.g., Ray)
  • Understanding of vehicle dynamics, motion planning, or multi-agent systems

Work Location: For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102665
Hiring Range for Job Opening
US Pay Range
$226,400-$271,700 USD