AI/ML Engineer

Responsibilities:

• Design, develop, and fine-tune

  transformer-based architectures

  (e.g., BERT, GPT, LLaMA, T5) for various NLP tasks.
• Implement

  reinforcement learning (RL) algorithms

  such as PPO, A3C, or DQN for optimizing large-scale models.
• Conduct experiments for

  model fine-tuning and evaluation

  , ensuring optimal performance on real-world data.
• Work on

  prompt engineering, instruction tuning, and alignment

  of LLMs using techniques like RLHF.
• Collaborate with cross-functional teams (product, data science, and engineering) to deliver scalable ML solutions.
• Research and stay up-to-date with

  state-of-the-art techniques

  in transformers, generative AI, and RL.
• Optimize models for

  efficiency and deployment

  , leveraging quantization, pruning, or distillation.

Requirements:

• 3+ years

  of hands-on experience in machine learning, with a focus on NLP and reinforcement learning.
• Strong expertise in

  transformer architectures

  and libraries such as

  Hugging Face Transformers, PyTorch, or TensorFlow

  .
• Proven experience in

  fine-tuning large language models (LLMs)

  and optimizing training pipelines.
• In-depth understanding of

  reinforcement learning algorithms

  and real-world RL applications.
• Experience with

  distributed training

  and large-scale data pipelines.
• Proficiency in Python and ML frameworks like

  PyTorch, TensorFlow, or JAX

  .
• Strong knowledge of cloud platforms (AWS, GCP, Azure) and ML Ops practices.
• Advanced degree (Master’s/PhD) in Computer Science, AI, Machine Learning, or a related field.