Senior Machine Learning Engineer

There is energy here…energy you can feel crackling at any of our international locations. It’s an energy generated by enthusiasm for our work, for our teams, for our results, and for our customers. Lattice is a worldwide community of engineers, designers, and manufacturing operations specialists in partnership with world-class sales, marketing, and support teams, who are developing programmable logic solutions that are changing the industry. Our focus is on R&D, product innovation, and customer service, and to that focus, we bring total commitment and a keenly sharp competitive personality.

Energy feeds on energy. If you flourish in a fast paced, results-oriented environment, if you want to achieve individual success within a “team first” organization, and if you believe you can contribute and succeed in a demanding yet collegial atmosphere, then Lattice may well be just what you’re looking for.

As a senior member of the team, you will be responsible for developing neural network models for edge inference on Lattice sensAI solutions. You will explore latest network architectures, ML operations, quantization methods, optimization techniques to make inferencing efficient on Lattice sensAI solutions.

You need to bring a strong set of skills related to development of neural networks for video/image applications. Experience in training models for applications like object detection, classification, segmentation is also required for this position. You will work closely with software and hardware teams to implement optimized models that serve as benchmarks for our sensAI ML compiler and will be integrated into our Model Zoo.

Key Skills and Responsibilities:

• Design and implement reference NN models using Keras, TensorFlow, PyTorch and ONNX.

• Design models that cover a wide range of architectures, including CNNs, RNNs, Transformers, and hybrid models.

• Optimize models for deployment on different hardware platforms, ensuring efficient inference performance.

• Work closely with the ML compiler team to identify performance bottlenecks and suggest model-specific optimizations.

• Develop and maintain a Model Zoo containing pre-trained, optimized, and quantized models for customers.

• Stay updated with the latest advancements in neural network architectures and model optimization techniques.

• Collaborate with software and hardware teams to ensure seamless integration of reference models into the ML compiler workflow.

• Help create test cases and datasets for evaluating compiler optimizations and accuracy.

Education and General:

• 6 to 12 years of experience in developing and optimizing neural network models.

• Proficiency in deep learning frameworks such as TensorFlow, Keras, and ONNX.

• Strong understanding of model architectures, including CNNs, RNNs, Transformers, and attention mechanisms.

• Experience with model quantization, pruning, and hardware-aware optimization.

• Experience with Python programming and deep learning libraries (e.g., NumPy, TensorFlow, ONNX Runtime).

• Hands-on experience with model conversion tools such as tf2onnx, ONNX converters, and PyTorch exporters.

• Experience working with ML hardware accelerators (e.g., TPUs, NPUs, custom AI chips).

• Strong debugging and troubleshooting skills for model validation and performance tuning.

• Excellent communication skills and ability to collaborate with cross-functional teams.

• Programming in C/C++ and OpenCV is a plus

Key Words:

• Keras, TensorFlow, PyTorch, ONNX

• Neural Network creation, optimization, training

• Embedded vision, image processing

• ML compiler

• Python, C/C++