Machine Learning Engineer

5 days ago

Gurgaon, Haryana, India beBee Careers Full time

We're looking for an expert in Generative AI and Large Language Models to join our team. The ideal candidate should have a proven track record of developing, fine-tuning, and deploying state-of-the-art models like GPT, BERT, T5, and similar architectures.

Key Responsibilities
  • Developing AI Models: Create and optimize generative models, focusing on LLMs (e.g., GPT, BERT, T5) for various NLP tasks such as text generation, summarization, sentiment analysis, and question answering.
  • Data Preparation: Work with large-scale datasets to train and fine-tune models, ensuring high-quality data preprocessing and augmentation to improve model accuracy and performance.
  • Optimizing Algorithms: Collaborate with cross-functional teams to design and implement algorithms that scale and are optimized for production environments.
  • Deploying Models: Lead efforts in deploying machine learning models to production and optimizing for performance, efficiency, and scalability on cloud infrastructure.
  • Collaborating with Teams: Work closely with product, engineering, and data science teams to align AI solutions with business goals and requirements.
  • Staying Up-to-date: Stay current with the latest advancements in AI, machine learning, and NLP. Contribute to research papers or patents where applicable.
  • Mentoring Junior Team Members: Mentor junior engineers and data scientists, sharing your expertise in machine learning, AI tools, and education.
Requirements
  • A Bachelor's or Master's degree from a premier institution in Computer Science, Engineering, Mathematics, or a related field is required.
  • At least 3-6 years of professional experience working in Generative AI, Natural Language Processing (NLP), and deep learning is necessary.
  • Hands-on experience with training, fine-tuning, and deploying Large Language Models (LLMs) such as GPT, BERT, T5, etc. is essential.
  • A strong understanding of transformer architectures, attention mechanisms, and neural networks is crucial.
  • Experience with state-of-the-art NLP techniques (text generation, embeddings, sentiment analysis, etc.) is preferred.
Technical Skills
  • Proficiency in Python and popular machine learning libraries (TensorFlow, PyTorch, Hugging Face, etc.).
  • Deep understanding of data structures, algorithms, and machine learning methodologies.
  • Familiarity with cloud platforms (AWS, GCP, Azure) for model deployment and scaling.
  • Experience in optimizing models for production environments (efficiency, latency, etc.).

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