Senior Machine Learning Developer

Job summary

Lead the development of model architectures and AI roadmaps for perception, classification, and segmentation within the NovAI intelligence suite. Integrate machine learning outputs with robotic controllers and optimize models for real-time edge implementation.

Job details

Role Summary: Our never-before-seen, adaptive welding products push the limit of what physical AI in general, and machine learning in particular, can do today. We are looking for an experienced and hands-on Senior Machine Learning Developer to drive perception, classification, segmentation, and advanced AI features for our NovAI intelligence suite. As a Senior Machine Learning Developer, reporting to the Development Manager of AI/Robotics, you will lead model architecture development, decide on machine learning technology roadmaps, and serve as a critical technical leader across our AI and robotics teams. Key Responsibilities : - Model Development & Research Participate in technical interviews, onboarding, and mentoring to help build and scale the machine learning engineering team. Build, train, and evaluate computer vision/ML models (detection, segmentation, tracking, pose estimation, image fusion) using PyTorch and TensorFlow. Fine-tune neural network architectures (CNN, RNN, Transformer) and classical ML methods for real-time welding process sensing. Define short and long-term machine learning technology roadmaps, lead fast prototyping, and select AI tools and framework architectures. Implement vision-language-action (VLA) models and foundation architectures for spatial reasoning and multi-modal perception. Develop and integrate world models for predictive perception, spatial reasoning, and dynamic environmental simulation in adaptive welding scenarios. Develop closed-loop reinforcement learning (RL), imitation learning, and continuous learning policies for complex control tasks, adaptive manipulation, and robotic feedback loops. Architect simulation-to-real (Sim2Real) pipelines and synthetic data workflows (Isaac Gym, MuJoCo) to accelerate domain randomization - Physical AI & Robotics Integration Fuse vision, arc, and thermal sensor data to enable real-time robotic decision-making. Integrate ML outputs with motion control, PLCs, and robot controllers within target latency, power, and compute budgets. Support toolpath and trajectory optimization for stress reduction, energy efficiency, and faster cycle times. - Deployment, Testing & MLOps Optimize models for real-time edge implementation and maximize hardware efficiency using quantization, pruning, TensorRT, and ONNX Runtime on embedded platforms. Validate and troubleshoot end-to-end integrations across software and hardware stack components. Maintain state machine documentation, architecture diagrams, technical specifications, and user guides. Provide onsite and remote commissioning support during customer installations. Implement robust MLOps practices, including automated model versioning, validation workflows, and monitoring (W&B/MLflow). - Cross-Functional Collaboration Partner with controls and welding engineering teams to integrate robotic systems with external automation hardware. Get to the root of one-time and repeating integration or customer Service issues and implement long-term, sustainable solutions. Contribute to scientific publications and patent applications; evaluate emerging ML tooling and frameworks. Travel as required to customer deployment sites or industry conferences. Qualifications and Experience : Bachelor's degree in CS, Electrical Engineering, Software Engineering, or related field (Master's preferred). 5+ years of practical experience with PyTorch, TensorFlow, and OpenCV. 3+ years of experience with deep learning frameworks (TensorFlow, Keras, PyTorch). Strong foundation in supervised/unsupervised learning, deep neural networks (CNNs/RNNs), and transfer learning. Solid computer vision skills: image processing, object detection, segmentation, and feature extraction. Proficiency in C++ and Python applied to robotic systems. Strong technical documentation, communication, and Git-based workflow skills. Strategic, critical thinking, and analytical skills for structured problem-solving rather than band-aid fixes Preferred Additional Qualifications: Experience integrating an AI pipeline with a third party PC/PLC Hands-on exposure to edge inference optimization or Physical AI systems. Familiarity with industrial sensing or automated welding processes Commitment to Novarc Values: Demonstrate and embed Novarc’s core values of Hungry, Humble, and Smart in daily work, decision-making, collaboration, and interactions with colleagues, customers, and partners. Hungry: Be Passionate, Never Give Up, Customer Focused, Continuous Learning, Do What You Say Humble: Servant Leader, No arrogance, Less Ego, Listen > Talk Smart: High EQ, Challenge the Status Quo, Thought Leaders

What you’ll do

Lead the development of model architectures and AI roadmaps for perception, classification, and segmentation within the NovAI intelligence suite. Integrate machine learning outputs with robotic controllers and optimize models for real-time edge implementation.

Requirements

Requires a Bachelor's degree in CS or Engineering with over 5 years of experience in PyTorch, TensorFlow, and OpenCV. Candidates must be proficient in C++ and Python with a strong foundation in deep neural networks and computer vision.

Listed skills

• C++ · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• PyTorch
• TensorFlow
• OpenCV
• C++
• Python
• Computer Vision
• Deep Learning
• Reinforcement Learning
• MLOps
• Edge Inference Optimization
• Robot Control
• Model Architecture
• Image Segmentation
• Object Detection
• Sim2Real
• TensorRT

Job areas

• Engineering
• Technology
• Software
• Manufacturing
• Data & Analytics