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Remote Video Encoding Jobs in Chicago, IL (NOW HIRING)

Video Streaming & Encoding: experience with real-time video transport protocols such as RTSP and ... Remote Troubleshooting and Fleet Management: track record of diagnosing and resolving hardware and ...

Technical Art Director

Chicago, IL · On-site +1

$127K - $147.30K/yr

Chicago, IL (or remote for extremely well-qualified candidates) Office : 3 days/week in South Loop ... Principal, Video Team Employment Type: Fixed-term, benefits eligible, contract through end of 2026 ...

Remote Video Encoding information

See Chicago, IL salary details

$63.4K

$130.8K

How much do remote video encoding jobs pay per year?

As of May 31, 2026, the average yearly pay for remote video encoding in Chicago, IL is $127,276.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,700.00 and $129,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Video Encoding Specialist, and why are they important?

To thrive as a Remote Video Encoding Specialist, you need a strong understanding of video formats, compression techniques, and digital media workflows, often supported by relevant experience or a technical degree. Familiarity with encoding tools such as Adobe Media Encoder, FFmpeg, or HandBrake, as well as knowledge of video streaming platforms and codecs, is essential. Strong attention to detail, time management, and problem-solving abilities are valuable soft skills in this role. These skills ensure high-quality video output, efficient project turnaround, and reliable delivery of content to various platforms.

What are some common challenges faced by professionals in remote video encoding roles, and how can they be addressed?

One common challenge in remote video encoding is ensuring consistent video quality while managing large file transfers over varying internet connections. Working remotely may also require troubleshooting encoding software or hardware issues without on-site IT support. To address these challenges, it's important to maintain up-to-date encoding tools, establish efficient file transfer protocols (such as FTP or cloud storage), and participate in regular team check-ins to align on project requirements. Collaborating closely with editors, producers, and IT teams through communication platforms helps resolve issues quickly and ensures project deadlines are met.

What is remote video encoding?

Remote video encoding is the process of converting video files from one format to another using computers or servers that are accessed over the internet, rather than on-site hardware. This allows companies or individuals to upload their video files to a remote server, where the files are processed and optimized for different devices or platforms. Remote encoding is commonly used for streaming services, content delivery networks, and video production workflows, as it saves time and computing resources for users. It also enables easier scaling and collaboration for teams working in different locations.

What is the difference between Remote Video Encoding vs Remote Video Editing?

AspectRemote Video EncodingRemote Video Editing
Required SkillsVideo codecs, compression, file formatsCutting, transitions, effects
Tools UsedEncoding software, media serversEditing software like Adobe Premiere, Final Cut
Work EnvironmentServer-based, technical setupCreative, timeline-based
Industry UsageBroadcast, streaming servicesFilm, TV, online content

Remote Video Encoding focuses on converting and compressing video files for optimal playback and streaming, requiring technical knowledge of codecs and formats. Remote Video Editing involves creatively assembling footage, adding effects, and refining videos. While both roles require video expertise, encoding is more technical and process-oriented, whereas editing emphasizes creative storytelling and visual design.

What are the most commonly searched types of Video Encoding jobs in Chicago, IL? The most popular types of Video Encoding jobs in Chicago, IL are:
What are popular job titles related to Remote Video Encoding jobs in Chicago, IL? For Remote Video Encoding jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Video Encoding jobs in Chicago, IL look for? The top searched job categories for Remote Video Encoding jobs in Chicago, IL are:
Senior Embedded Systems Engineer

Senior Embedded Systems Engineer

Loadsmart

Chicago, IL • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday


Job description

ARE YOU INTERESTED IN JOINING AN INNOVATIVE LOGISTICS TECHNOLOGY COMPANY?
Loadsmart is a growth-stage technology company valued at over $1 billion (a true Tech Unicorn)!
We are a collection of industry veterans and user-centered engineers using innovative technology to fearlessly reinvent the future of freight by helping shippers, brokers, warehouses and carriers to move more with less.
With headquarters in Chicago and a globally distributed remote team, Loadsmart continues to attract top talent committed to driving meaningful change. We seek professionals who embody our core values: curiosity, clarity, results, commitment, and teamwork.
We are looking for an Embedded Systems Engineer to join our SmartGate team. SmartGate is Loadsmart's Physical AI platform for warehouses and distribution centers - computer vision systems deployed at customer gates that automatically identify trucks, capture license plates and DOT numbers, automate check-ins, and feed real-time data into Opendock, our dock and yard management platform. The technology runs on NVIDIA Jetson edge compute devices paired with AXIS IP cameras, packaged in self-contained outdoor enclosures with LTE connectivity and power systems designed to operate reliably in all conditions, including solar-powered installations. This is a fast-paced, deadline-driven role: this engineer owns the full hardware-software integration layer, including the edge software stack, compatibility validation, fleet reliability, and remote troubleshooting. Physical installation at customer sites is performed by contractors.
DEPARTMENT: Engineering
LOCATION: United States (Remote)
WHAT YOU GET TO DO:
  • Maintain end-to-end system integrity across the SmartGate hardware-software stack: AXIS IP cameras, NVIDIA Jetson edge compute devices, Savant video pipeline, LTE modems, routing hardware, outdoor enclosures, and power systems; test new hardware generations, firmware versions, and software releases against the production stack before fleet-wide rollout
  • >
  • Build, configure, and validate complete hardware kits ahead of customer deployments; verify power budget compliance for solar-capable configurations; coordinate with installation contractors on setup expectations and post-install validation
  • >
  • Deploy and update SmartGate software across 30+ edge and cloud gates using the Ansible-based Fleet Management system; manage hardware inventory and prepare Jetson and camera kits for shipment to new sites
  • >
  • Remotely diagnose and resolve failures across the deployed fleet, including Savant pipeline lockups, camera connectivity issues, and networking misconfigurations; perform on-site visits when remote resolution is not achievable
  • >
  • Develop and maintain commissioning runbooks and validation procedures; collaborate with the Computer Vision team on hardware-side model validation and root cause analysis for missed or incorrect gate events
  • >
  • Test and benchmark which SmartGate pipeline workloads can run directly on AXIS camera hardware versus the Jetson; AXIS cameras include the ARTPEC-8 chip with an onboard AI inference engine (Larod) and support custom applications via the AXIS Camera Application Platform (ACAP).
  • >

REQUIRED QUALIFICATIONS:
  • Linux: 2+ years of production experience with embedded or server-side Linux, including service configuration, log analysis, and process-level debugging; NVIDIA Jetson experience is a strong plus
  • >
  • Scripting: 2+ years writing Python and/or Bash for production use, including diagnostic tools and operational automation in Linux or embedded environments
  • >
  • Networking: working knowledge of IP networking (subnets, VLANs, DNS, routing, firewalls) and cellular/LTE; able to independently isolate and resolve edge-to-cloud connectivity failures
  • >
  • Hardware Integration: production experience integrating edge compute platforms (NVIDIA Jetson or comparable), IP cameras, and supporting hardware into validated, production-ready systems; working knowledge of DC power constraints and solar-capable configurations
  • >
  • IP Camera Systems: experience configuring, testing, and troubleshooting IP cameras in production environments; familiarity with camera-side compute capabilities and the distinction between on-camera and edge-device workloads
  • >
  • Video Streaming & Encoding: experience with real-time video transport protocols such as RTSP and SRT, including configuring, and troubleshooting. Able to diagnose streaming issues and instability across edge and cloud systems. Comfortable working across the full video pipeline, from camera output through network transport to decoding and visualization.
  • >
  • Video and Image Encoding Fundamentals: Understanding of modern video codecs such as H.265/HEVC and their trade-offs in compression efficiency, bandwidth usage, latency, and compute requirements. Familiar with key encoding parameters (bitrate, GOP structure, profiles, presets) and how they impact image quality, artifacting, and system performance. Strong grasp of image fundamentals including resolution, pixel density, compression formats, and file size implications, with the ability to make informed decisions balancing visual quality, storage, and transmission constraints in edge-based computer vision systems.
  • >
  • Remote Troubleshooting and Fleet Management: track record of diagnosing and resolving hardware and software failures without physical device access; experience with Ansible or comparable tools for managing remote device fleets
  • >
  • Communication: ability to document technical findings clearly and coordinate with contractors, engineering teammates, and customer contacts.
  • >

PREFERRED QUALIFICATIONS:
  • Familiarity with edge AI inference pipelines such as NVIDIA DeepStream, Savant, TensorRT; model training is not required
  • >
  • Experience with AXIS camera systems and the AXIS Camera Application Platform (ACAP)
  • >
  • Experience with Docker in embedded or edge computing environments
  • >
  • Background in logistics, warehousing, or industrial technology is a plus
  • >
  • Experience authoring operational documentation, kit validation procedures, or runbooks in an environment where processes are being built from scratch.
  • >

$134,000 - $210,000 a year
The compensation offered for this role will be based on multiple factors such as location, the role's scope and complexity, the candidate's experience and expertise. In addition to your base compensation offer, this role is eligible for an incentive bonus, you will also receive stock options and benefits listed below.
WORKING AT LOADSMART:
• Competitive base salaries - we believe in rewarding top talent
• Extremely competitive Equity package - become a shareholder in our company!
• Loadie Time Off - PTO and sick days without a limit
• Comprehensive Medical, Dental, and Vision insurance plans
• 401k Match
*Applicants must be currently authorized to work in the United States on a full-time basis. Loadsmart will not sponsor applicants for work visas.
At Loadsmart, we believe our biggest asset is our people. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. Loadsmart treats all candidates and employees with respect and does not discriminate in our recruiting, hiring, and promoting processes, including on the basis of race, color, religion, sex, age, sexual orientation, gender identity and/or expression, national origin, veteran status, or disability.
It is the policy of Loadsmart that all offers of employment made shall be contingent upon successful completion of electronic background check(s). These checks will be job-related, consistent with business necessity and conducted by our vendor, pursuant to all applicable laws, rules, policies and procedures of our candidates' specific locale.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.