AI/ML Engineer – Time Series & Robotics

SR Staffing; Houston (TX); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Competitive base salary

Benefits package

Job summary

SR Staffing in Houston is seeking an AI/ML Engineer to develop and deploy machine learning algorithms for multi-sensor time-series data from vehicles and robotic platforms. You will collaborate with robotics, controls, and embedded systems teams to build robust models.

The role emphasizes prototyping in Python with PyTorch/TensorFlow and translating prototypes into production-ready C++ code. You will evaluate model performance, improve robustness across platforms, and contribute to data

Qualifications

• Requires degree in CS/EE/Applied Math or related field.
• Experience with embedded/edge AI, model optimization, and deployment workflows.
• Hands-on ML experience with time-series or sensor data.
• Strong C++ skills and experience with modern ML frameworks.
• Experience handling real-world noisy data in automotive/robotics/IoT environments.
• Familiarity with NumPy, Pandas, and Jupyter workflows.
• Ability to communicate technical concepts across cross-functional teams.

Responsibilities

• Design ML models for time-series sensor data (currents, torques, IMUs, etc.).
• Build data pipelines for collection, preprocessing, feature extraction, labeling.
• Prototype algorithms in Python (PyTorch/TensorFlow) and collaborate with embedded engineers.
• Develop production-level models in C++ to improve runtime efficiency.
• Evaluate model performance and improve robustness across platforms.
• Collaborate with robotics and vehicle engineering teams to translate requirements into ML solutions.
• Support data visualization, dashboards, and internal tools for model outputs.
• Document models, experiments, datasets, and results for reproducibility.

Skills

Embedded AI

Edge AI

Model compression

Time-series ML

C++

ML frameworks

Noisy data handling

NumPy/Pandas/Jupyter

Cross-functional collaboration

Real-world data experience

Education

Bachelor's/Master's/PhD in CS/EE/Applied Math

Tools

PyTorch

TensorFlow

ROS

Jupyter

Job description

The AI/ML Engineer will develop and deploy machine learning algorithms that analyze multi-sensor time-series data from vehicles and robotic platforms. This position focuses on building robust models that improve system performance, monitoring, and intelligent behavior, working closely with robotics, controls, and embedded systems teams.

Key Responsibilities

• Design and implement ML models for time-series sensor data (e.g., currents, torques, IMUs, joint states, vehicle signals, cameras, GPS).
• Build and maintain data pipelines for collection, preprocessing, feature extraction, and labeling.
• Prototype algorithms in Python using frameworks such as PyTorch and TensorFlow, and collaborate with embedded engineers to create deployable, resource-efficient models.
• Develop production-level models in C++ to improve runtime efficiency and optimize resource utilization based on Python prototypes.
• Evaluate model performance using appropriate metrics and continuously improve robustness and generalization across platforms and applications.
• Work with robotics and vehicle engineering teams to translate business and technical requirements into machine learning solutions.
• Support data visualization, dashboards, and internal tools used to interpret model outputs and system behavior.
• Document models, experiments, datasets, and results to ensure reproducibility and traceability.

Required Qualifications

• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Experience with embedded AI, edge AI, or model compression and optimization techniques.
• Hands-on experience developing machine learning solutions for time-series or sensor data.
• Strong proficiency in C++ and modern machine learning frameworks.
• Experience working with real-world noisy data in environments such as automotive, robotics, industrial systems, or IoT.
• Familiarity with data science tools and workflows including NumPy, Pandas, and Jupyter.
• Ability to work effectively within cross-functional teams and communicate technical concepts clearly.

Preferred Qualifications

• Familiarity with control systems, robotics, or vehicle dynamics.
• Experience with MLOps tools, including experiment tracking, model versioning, and CI/CD pipelines for machine learning.
• Experience with ROS or other multimodal sensor data frameworks.
• Prior experience in a product development or R&D environment working with multidisciplinary teams.
• Competitive base salary plus benefits.
• Compensation will be determined based on factors such as market conditions, location, experience, skills, and job-related knowledge.
• Total compensation may include additional incentive or benefit programs, depending on the position.