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How much do the training loft jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for the training loft in the United States is $42.21, according to ZipRecruiter salary data. Most workers in this role earn between $27.88 and $53.85 per hour, depending on experience, location, and employer.

What is The Training Loft?

The Training Loft is a private fitness studio that offers personalized training programs, group fitness classes, and wellness coaching. Unlike large commercial gyms, The Training Loft focuses on individualized attention in a smaller, supportive environment. Clients work with professional trainers to achieve their health and fitness goals through customized workouts, nutritional guidance, and continuous motivation. The studio typically caters to people of all fitness levels, from beginners to advanced athletes, aiming to provide a welcoming and effective fitness experience.

What are the key skills and qualifications needed to thrive as a personal trainer at The Training Loft?

To thrive as a Personal Trainer at The Training Loft, you need a solid understanding of exercise science, program design, and anatomy, typically supported by certifications such as NASM or ACE. Familiarity with fitness assessment tools, workout tracking software, and gym equipment is essential. Exceptional interpersonal skills, motivation, and the ability to tailor communication to diverse clients make someone stand out in this role. These skills ensure safe, effective training programs and foster lasting client relationships that drive individual progress and business success.

What are some common challenges faced by personal trainers at The Training Loft, and how can they be addressed?

Personal trainers at The Training Loft often encounter challenges such as managing diverse client needs, maintaining client motivation, and balancing administrative tasks with training sessions. To address these, trainers typically develop strong communication skills, stay updated with the latest fitness techniques, and collaborate closely with colleagues to share best practices. The supportive team environment at The Training Loft encourages ongoing professional development and peer learning, helping trainers overcome challenges and excel in their roles.

What is the difference between The Training Loft vs Personal Trainer?

AspectThe Training LoftPersonal Trainer
CertificationsVarious fitness certifications, including NASM, ACE, or NASM-CPTTypically holds certifications like NASM-CPT, ACE, or ACSM
Work EnvironmentFitness studios, gyms, or private settingsGyms, private studios, or clients' homes
Industry UsageTraining programs, fitness classes, and workshopsOne-on-one or small group training sessions

The Training Loft generally refers to a fitness education provider or training facility offering certifications and courses, while a Personal Trainer is a certified professional providing individualized fitness coaching. Both roles require similar certifications and work in fitness environments, but The Training Loft focuses on education, whereas a Personal Trainer delivers direct client services.

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What cities are hiring for The Training Loft jobs?

Cities with the most The Training Loft job openings:

Infographic showing various The Training Loft job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 16% Part Time, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $87,800 per year, or $42.2 per hour.

Backend Engineer - Mission Operations Services

Loft Orbital Solutions

Golden, CO โ€ข On-site

$140K - $190K/yr

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Loft Orbital is looking for a Backend Engineer to join our Mission Operations Services (MOS) team. MOS owns the backend services that let Loft operators and customers command, monitor, and automate our satellite fleet through Cockpit, our mission control system. You'll help build and scale the microservices that sit between ground and flight software, turning high-level intent into safe, reliable on-orbit operations.
You'll work across multiple satellite platforms and collaborate closely with backend, flight software, embedded systems, test, and satellite operations teams. This is a hands-on engineering role where you'll both build new systems and help debug live missions. We also offer SatDevOps training, so you don't just write the tools - you actually use them to operate spacecraft.
If you're excited about building backend systems that directly control satellites - and you like the idea of both shipping code and helping fly missions - we'd love to hear from you.
About this Role
  • Design and build backend tools for operations: services that power passes, autopilots, activities, and day-to-day satellite operations.
  • Handle commands and telemetry across multiple satellite buses and ground segment providers, with a strong focus on safety, robustness, and observability.
  • Write production backend code in Python, owning services end-to-end from design and implementation through deployment and maintenance.
  • Collaborate with flight software, embedded software, integration and test, and space infrastructure teams to integrate new satellite buses and capabilities into Cockpit.
  • Support internal users of Cockpit (operators, test engineers, solutions engineers) by improving APIs, workflows, and debugging tools.
  • Have the opportunity to take part in spacecraft operations through SatDevOps rotations, occasionally helping investigate anomalies and supporting real-time incident response when needed.

Must Haves:
  • 4+ years of relevant backend software engineering experience in production environments
  • Solid Python development experience in a production environment.
  • Experience with Docker and container-based development.
  • Hands-on experience with backend web development frameworks (e.g., Django, Flask, FastAPI, etc.).
  • Proven API design skills (designing, documenting, and maintaining HTTP/GraphQL/REST-style APIs).

Nice to Haves:
  • Experience with Django and/or GraphQL.
  • Strong database fundamentals and practical experience (e.g., Postgres, time-series DBs).
  • Exposure to Kubernetes in production.
  • Familiarity with InfluxDB / TimescaleDB or other time-series systems.
  • Background in mission-critical, distributed, or real-time systems (space or otherwise).

$140,000 - $190,000 a year
State law requires us to share the posted base compensation range for this role. Final compensation will be determined based on your education, experience, knowledge, skills, and abilities. The salary range is intentionally broad to account for differences in experience and scope, as well as geographic market variations in pay. We evaluate each candidate individually to ensure alignment between their background, the role's responsibilities, and local market benchmarks. Most importantly, we are excited to meet you, and see if you are a great fit for our team. What we can't quantify for you are the exciting challenges, supportive team, and amazing culture we enjoy.
Who We Are: Founded in 2017, Loft provides governments, companies, and research institutions with a fast, reliable, and simple way to deploy missions in orbit.
We integrate, launch, and operate spacecraft, offering end-to-end missions as a service across Earth observation, IoT connectivity, on-orbit AI, national security missions, and more. Leveraging our existing space infrastructure and an extensive inventory of satellite buses, Loft is reducing years-long integration and launch timelines to months. With more than 30 missions flown, Loft's flight heritage and proven technologies enable customers to focus on their mission objectives.
With a growing fleet on track to reach 30 satellites by 2027, we are scaling up quickly across our offices in San Francisco, CA | Golden, CO | and Toulouse, France to meet accelerating demand for space infrastructure.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.