Embedded Machine Learning Engineer
Manchester Full-time Mid-level Machine Learning Engineering
At a glance
Mid-level Machine Learning Engineering role at DEKA Research & Development. Manchester · full-time · no salary stated · we estimate $144,250–$228,825 across the United States.
Estimated pay
DEKA Research & Development has not published a salary for this role. The figure below is our estimate, not theirs.
$144,250 – $228,825
What the middle half of mid-level machine learning engineering roles in the United States paid, among postings that did state a salary.
Worked out from 295 postings that stated pay, median $188,950. Last updated Oct 31, 2026.
RoleMachine Learning Engineering
SeniorityMid-level
LocationManchester
EmploymentFull-time
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build control, computer vision and sensor-fusion algorithms for robotic systems
- Write production software in Python and C++, including robot detection algorithms using Robot Operating System
- Create machine-learning workflows for training and deployment, plus models for regression, detection and volumetric estimates
- Optimize machine-learning code for embedded and hardware-accelerated devices
- Develop low-memory, power-efficient C++ libraries that support communication between processes
What you bring
- A master’s in computer science, robotics engineering or a related engineering discipline, plus five years in robotics or control-system development
- Five years using Python and C++ and applying control and computer-vision algorithms with Robot Operating System
- Five years designing detection prototypes with sensor fusion, and four years building machine-learning training pipelines and algorithms
- Three years architecting software systems and optimizing machine-learning code for embedded or hardware-accelerated devices
- Two years developing efficient C++ inter-process communication libraries and one year writing software for medical devices
Who this fits
This mid-level role suits an engineer with a relevant master’s degree and substantial robotics, controls and machine-learning development experience. The work combines algorithm development, production coding, pipeline creation and deployment on embedded hardware.
From the employer
DEKA Research and Development is seeking Embedded Machine Learning Engineers (Multiple Openings) to join our engineering team.
Job Responsibilities:
Master’s degree, in Computer Science, Robotics Engineering, or related engineering discipline, or foreign degree equivalent, plus 5 years of experience in any suitable occupation related to the development of robotics or control systems.
The experience (which may be gained concurrently) must also include the following:
Job Responsibilities:
- Research and create linear/nonlinear and optimal control algorithms, computer vision algorithms, and sensor fusion algorithms (10%)
- Write production level code in Python and C++ (20%)
- Implement detection algorithms on a robot using Robot operating system (10%)
- Develop low memory and power efficient libraries for inter-process communication (5%)
- Develop pipelines for machine learning training and deployment (15%)
- Develop machine learning algorithms for regression, detection and volumetric estimation (20%)
- Develop an optimized machine learning code for deployment on embedded devices and hardware accelerated devices (20%)
Master’s degree, in Computer Science, Robotics Engineering, or related engineering discipline, or foreign degree equivalent, plus 5 years of experience in any suitable occupation related to the development of robotics or control systems.
The experience (which may be gained concurrently) must also include the following:
- 5 years of experience with use of controls and computer vision algorithms in robotics and Robot Operating System;
- 5 years of experience with software skills in Python and C++;
- 5 years of experience developing and designing prototype devices for detection using sensor fusion techniques;
- 4 years of experience developing pipelines for machine learning training;
- 4 years of experience developing machine learning algorithms for regression, detection, segmentation and volumetric estimation;
- 3 years of experience architecting systems using software development skills;
- 3 years of experience developing optimized machine learning code for deployment on embedded and hardware accelerated devices;
- 2 years of experience developing low memory and power efficient C++ libraries for inter-process communication; and
- 1 year of experience with software development for medical devices.
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