Senior Machine Learning Developer

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