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Machine Learning Engineer
Spx Technologies
Design, train, and deploy CV/ML models for defect detection on embedded/robotic platforms.
7d ago
Experienced (8-12 years), Junior (1-3 years), Expert & Leadership (13+ years)
Full Time
Greater Orlando
Office Full-Time
Company Size
5,000 Employees
Service Specialisms
Engineering
Design
Technical Services
Consulting
Project Management
Sector Specialisms
HVAC
Detection and Measurement
Infrastructure Equipment
Heating
Ventilation
Air Conditioning
Residential Boilers
Commercial Boilers
Role
What you would be doing
model optimization
dataset curation
ci‑cd pipelines
deep learning
3d localization
robotics integration
- Convert and optimize models for embedded inference using tool such as TensorRT, ONNX, NVIDIA Jetson, Intel OpenVINO.
- Curate, Manage, and augment large video / image datasets; define labeling guidelines and manage annotation workflows (Labelbox, etc.).
- Design custom metrics to evaluate model performance in the field
- Build reproducible training / CI‑CD pipelines with Docker, GitHub Actions, PyTorch Lightning, and MLflow; automate experiment tracking and model registry.
- Design, implement, and optimize deep‑learning models using tools such as YOLOv_, Faster R‑CNN, Mask R‑CNN, PyTorch, for multi‑class defect detection, segmentation, and severity grading of imagery.
- Integrate non-depth-camera and depth‑camera inputs to enhance 3‑D localization of defects; implement calibration, rectification, triangulation, and point‑cloud fusion pipelines.
- Tune hyper‑parameters, perform ablation studies, and apply automated model‑selection / NAS techniques to maximize precision‑recall under real‑time constraints.
- Collaborate with robotics engineers to integrate models into the real-world systems.
What you bring
linux
docker
python
c++
deep learning
bachelor's
- Fluency in Linux development, Git‑based workflows, CMake, and containerization (Docker/Podman).
- Ability to travel occasionally (domestic and international) to test sites and customer locations.
- Proven record of shipping CV/ML models into production on robotic, embedded, or edge‑AI platforms.
- Bachelor’s in Computer Science, Computer Engineering, or Electrical Engineering required.
- Hands‑on experience with object detection and segmentation architectures (YOLO, DETR, EfficientDet, etc.).
- Experience with 3‑D reconstruction, point‑cloud processing (PCL, Open3D), or LiDAR fusion.
- Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust)
- Hybrid Role, Minimum 3 days in office per week.
- Travel up to 10%
- Strong understanding of camera physics, image formation, stereo geometry, and depth estimation.
- Excellent verbal and written communication skills in English; able to convey complex ML concepts to cross‑functional audiences.
- 5+ of professional software experience, including 3+ years focused on deep learning / computer vision.
- Master’s in Computer Science, Computer Engineering, or Electrical Engineering preferred.
- Generous and flexible paid time off including paid personal time off, caregiver, parental, and volunteer leave
- Educational assistance, leadership development programs, and recognition programs
- Competitive health insurance plans and 401(k) match, with benefits starting day one
- Bonus Computer Vision
- Competitive and performance-based compensation packages and bonus plans
Information not given or found
Interview process
Information not given or found
Visa SponsorshipInformation not given or found
Security clearanceInformation not given or found
Company
Overview
- Founded with a focus on providing cutting-edge engineering solutions, the company has become a leader in industrial technology.
- Specializing in sectors like energy, industrial, and infrastructure, they create impactful, customized solutions.
- The company's portfolio includes equipment and services that support essential industries like energy generation, utilities, and water resources.
- Known for their deep technical expertise, they excel in solving complex challenges that drive global industries forward.
- A leader in advancing power and energy systems, including renewable and traditional energy sources.
- With decades of experience, they have earned a reputation for quality and reliability in large-scale infrastructure projects.
- Their engineers and designers consistently deliver innovative solutions that enhance the efficiency, safety, and sustainability of critical systems.
- Integrity: Do what’s right, the right way. Both the “what” and the “how” matter.
- Accountability: Take ownership. Create understanding and develop solutions by communicating with data and transparency.
- Excellence: Exceed customer expectations through active engagement, relentless focus, and a passion for innovative solutions. Drive constant improvement in everything we do.
- Team Work: Engage. Have fun. Make others successful. Our strongest asset is the power of “we”.
- Results: Make an impact. Focus on what matters. Deliver on commitments.
30% by 2030
GHG Emissions Intensity Target
Aims to reduce Scope 1 and 2 greenhouse gas emissions intensity by 30% compared to 2019 levels.
7th annual report
Sustainability Progress Report
Documents further reductions in greenhouse gas intensity, with progress exceeding initial timelines.
31.2 M kg CO₂e
GHG Emissions (CO₂e)
Total greenhouse gas emissions in 2023, down from ~34.1 M kg CO₂e in 2022.
0.0197 kg CO₂e
Emissions Intensity per Revenue
GHG emissions intensity in 2023, reflecting significant improvement compared to 2018 levels.
- Green manufacturing initiatives at Cooling Towers include energy-efficient evaporative cooling HQ, plume-abatement tech saving up to 30% water, switching to VOC-free film-fill.
Jan 2023
Annual Reporting Start
The company began reporting annually on its D&I disclosures starting from January 2023.
- No quantified gender stats publicly disclosed beyond commitment to transparency in 2023 ESG reporting.
- D&I transparency is integrated into company reporting process (annual disclosures planned).
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