Senior Machine Learning Engineer

2 days ago

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1001 - 5000

💰 $50M Venture Round on 2009-08

Description

• Design and Build ML Models: Develop and implement advanced machine learning models (including deep learning architectures) for generative tasks, such as text generation, image synthesis, and other creative AI applications. • Optimize Generative AI Models: Enhance the performance of models like GPT, VAEs, GANs, and Transformer architectures for content generation, making them faster, more efficient, and scalable. • Data Preparation and Management: Preprocess large datasets, handle data augmentation, and create synthetic data to train generative models, ensuring high-quality inputs for model training. • Model Training and Fine-tuning: Train large-scale generative models and fine-tune pre-trained models (e.g., GPT, BERT, DALL-E) for specific use cases, using techniques like transfer learning, prompt engineering, and reinforcement learning. • Performance Evaluation: Evaluate models’ performance using various metrics (accuracy, perplexity, FID, BLEU, etc.), and iterate on the model design to achieve better outcomes. • Collaboration with Research and Engineering Teams: Collaborate with cross-functional teams including AI researchers, data scientists, and software developers to integrate ML models into production systems. • Experimentation and Prototyping: Conduct research experiments and build prototypes to test new algorithms, architectures, and generative techniques, translating research breakthroughs into real-world applications. • Deployment and Scaling: Deploy generative models into production environments, ensuring scalability, reliability, and robustness of AI solutions in real-world applications. • Stay Up-to-Date with Trends: Continuously explore the latest trends and advancements in generative AI, machine learning, and deep learning to keep our systems at the cutting edge of innovation.

Requirements

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field. • 3-5+ years focus on Machine Learning. • 5+ years overall software engineering in production • Proven experience with generative AI models such as GPT, VAEs, GANs, or Transformer architectures. • Strong hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. • Expertise in Python and libraries such as NumPy, Pandas, Scikit-learn. • Experience with Natural Language Processing (NLP), image generation, or multimodal models. • Familiarity with training and fine-tuning large-scale models (e.g., GPT, BERT, DALL-E). • Knowledge of cloud platforms (AWS, GCP, Azure) and ML ops pipelines (e.g., Docker, Kubernetes) for deploying machine learning models. • Strong background in data manipulation, data engineering, and working with large datasets. • Strong coding experience in Python, Java, Go, C/C++, R. • Good data skills – SQL, Pandas, exposure to various SQL and no SQL data bases. • Solid development experience with dev cycle on Testing and CICD. • Strong problem-solving abilities and attention to detail. • Excellent collaboration and communication skills to work effectively within a multidisciplinary team. • Proactive approach to learning and exploring new AI technologies.