Machine Learning Engineer
Develops, optimizes, and deploys deep learning models for autonomous vehicles and robots, managing large datasets and training pipelines. Requires 3+ years experience with PyTorch/TensorFlow, Python, and expertise in computer vision or LLMs.
About the job
What You'll Do
- Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle’s surroundings or predicting the intentions of other road users.
- Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
- Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
- Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
- Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
- Collaborate with Cross-Functional Teams: Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems.
What You'll Need
- Strong understanding of fundamental machine learning algorithms and neural network techniques.
- Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
- At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
- Working knowledge of C++ and SQL.
- Ability to quickly absorb new concepts by reviewing research papers, technical reports, and documentation.
- Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Nice to Have
- Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
- Experience developing ML algorithms for autonomous vehicles or robotics applications.
- Familiarity with neural network deployment and optimization tools such as triton, TensorRT, or similar frameworks.
- Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
- Experience working in cross-functional teams within a multidisciplinary environment.
- Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.
Skills
PyTorch, TensorFlow, JAX, Pyspark, NumPy, Scipy, Python, C++, SQL, TensorRT, Triton, Convolutional Neural Networks, Transformers, Multimodal Large Language Models
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