Mid Level Software Integration Engineer Jobs
Mid level software integration engineer jobs go to engineers ready to own integration projects end to end, make architectural decisions with limited oversight, and bring junior teammates up to speed. Openings are split across on-site, remote, and hybrid settings, concentrated in Automotive, Aerospace & Defense, and Technology & Software, with employers like 42dot, Apple, and PlusAI hiring at this level now.
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Showing 5 of 6+ Mid Level Software Integration Engineer jobs
INTRODUCTION
We are looking for the best
About us
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.
About The Role
Great models are only as good as the system they run on. This role sits at the boundary between the ML autonomy team's models and the on-board system, taking what the research and ML teams build and turning it into something that runs reliably, in real time, on real vehicle hardware. 42dot is looking for builders who want to own the last and hardest mile between a model that works in an offline eval and a model that works in a vehicle.
Founding Team Opportunity
The On-board Integration Architecture Is Being Defined Right Now, With No Legacy Deployment Stack To Retrofit. An Early Hire Here Will Help Shape
- The model deployment pipeline, from training-time artifact to vehicle-ready binary
- Inference optimization strategy and tooling for the whole autonomy stack
- The interface contract standard between ML models and on-board software
Responsibilities
- Integrate ML models (end-to-end driving, VLA, world models) onto the on-board compute and runtime stack
- Optimize model inference for latency, throughput, memory, and power on embedded automotive hardware
- Build and maintain the model deployment pipeline, including conversion, validation, and rollout
- Stabilize on-vehicle ML execution by diagnosing runtime failures, timing violations, and resource contention
- Define interface contracts between ML models and the rest of the on-board software stack
- Work closely with the ML autonomy team to close the loop between deployment constraints and model design
Qualifications
- A track record of grit and ownership, with success moving difficult problems from ambiguity to successful deployment
- Bachelor's, Master's, or PhD in CS, EE, Robotics, or related field
- 5+ years of experience in systems or software engineering, with meaningful time in ML inference, embedded systems, or real-time software
- Experience deploying and optimizing ML models in production, including on resource-constrained hardware
- Strong C++ and Python skills, with experience working across the ML and systems boundary
Preferred Qualifications
- Background in autonomous driving or robotics on-board software
- Experience with inference optimization frameworks such as TensorRT, ONNX Runtime, and automotive SoCs
- Experience with real-time operating systems and safety-critical software practices
- Experience building CI/CD and automated validation pipelines
INTRODUCTION
We are looking for the best
About us
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.
About The Role
Great models are only as good as the system they run on. This role sits at the boundary between the ML autonomy team's models and the on-board system, taking what the research and ML teams build and turning it into something that runs reliably, in real time, on real vehicle hardware. 42dot is looking for builders who want to own the last and hardest mile between a model that works in an offline eval and a model that works in a vehicle.
Founding Team Opportunity
The On-board Integration Architecture Is Being Defined Right Now, With No Legacy Deployment Stack To Retrofit. An Early Hire Here Will Help Shape
- The model deployment pipeline, from training-time artifact to vehicle-ready binary
- Inference optimization strategy and tooling for the whole autonomy stack
- The interface contract standard between ML models and on-board software
Responsibilities
- Integrate ML models (end-to-end driving, VLA, world models) onto the on-board compute and runtime stack
- Optimize model inference for latency, throughput, memory, and power on embedded automotive hardware
- Build and maintain the model deployment pipeline, including conversion, validation, and rollout
- Stabilize on-vehicle ML execution by diagnosing runtime failures, timing violations, and resource contention
- Define interface contracts between ML models and the rest of the on-board software stack
- Work closely with the ML autonomy team to close the loop between deployment constraints and model design
Qualifications
- A track record of grit and ownership, with success moving difficult problems from ambiguity to successful deployment
- Bachelor's, Master's, or PhD in CS, EE, Robotics, or related field
- 5+ years of experience in systems or software engineering, with meaningful time in ML inference, embedded systems, or real-time software
- Experience deploying and optimizing ML models in production, including on resource-constrained hardware
- Strong C++ and Python skills, with experience working across the ML and systems boundary
Preferred Qualifications
- Background in autonomous driving or robotics on-board software
- Experience with inference optimization frameworks such as TensorRT, ONNX Runtime, and automotive SoCs
- Experience with real-time operating systems and safety-critical software practices
- Experience building CI/CD and automated validation pipelines
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Find JobsMid Level Software Integration Engineer Job Market
Who's Hiring
Top Industries Hiring
- Automotive
- Aerospace & Defense
- Technology & Software
- Electronics & Hardware
- Artificial Intelligence
Mid Level Software Integration Engineer Jobs: Frequently Asked Questions
How do I get a mid level software integration engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you led the integration work, resolved system conflicts independently, and delivered results without close supervision. In your resume and interviews, emphasize the APIs, middleware, or platforms you have worked with in depth, the cross-team coordination you have driven, and any measurable outcomes like reduced latency or fewer integration failures.
Which companies hire mid level software integration engineers?
Companies hiring mid level software integration engineers right now include 42dot, Apple, and PlusAI, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from both large enterprises managing complex systems across multiple platforms and mid-size technology companies scaling their integration infrastructure.
Are there remote mid level software integration engineer jobs?
Yes, remote work is well established at this level. About 0% of mid level software integration engineer openings are remote or hybrid as of November 2026, reflecting how integration work can be executed effectively without being on-site. Engineers with strong asynchronous communication skills and experience collaborating across distributed teams are particularly competitive for these roles.
How do I move up to a mid level software integration engineer role?
Moving from entry level to mid level takes deliberate depth-building over time. Focus on owning integration features rather than just completing assigned tasks, learning the systems around you well enough to anticipate failure points, and demonstrating that you can close a project without hand-holding. Measurable impact, such as improving reliability or cutting integration time, signals readiness for mid level responsibilities more convincingly than years alone.
Which industries hire the most mid level software integration engineers?
Mid Level software integration engineer roles concentrate in Automotive, Aerospace & Defense, and Technology & Software, based on current listings on Migrate Mate as of November 2026. These sectors rely on connecting diverse internal and third-party systems at scale, which creates sustained demand for engineers who can own integration work at the mid level.