We are seeking a talented and motivated Senior AI Engineer with 4+ years of industry experience. The successful candidate will be responsible for developing, maintaining, and optimizing machine learning models and pipelines and collaborating with cross-functional teams to innovate and solve new use cases.

REQUIRED QUALIFICATIONS

• 4+ years of hands-on industry experience in AI and Machine Learning
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields
• Familiarity with recommendation systems and large language models such as Claude, AWS Bedrock, GPT4o, etc.
• Experience in natural language processing (NLP) and image recognition models
• Proficiency in coding with ML platforms (e.g., TensorFlow, PyTorch)
• 3+ Years of Python experience
• Experience with Docker
• Strong understanding of basic ML techniques (e.g., supervised and unsupervised learning)
• Excellent problem-solving and analytical skills
• Ability to work collaboratively with cross-functional teams
• Effective communication skills for technical and non-technical audiences
• Willingness to learn and adapt to new technologies and challenges
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields
  Job Types: Full-time, Permanent
  Pay: $140,000.00-$216,000.00 per year

Benefits:

• Dental care
• Disability insurance
• Paid time off
• Vision care
• Work from home

Schedule:

• 8 hour shift
• Monday to Friday

Experience:

• AI & Machine learning: 4 years (required)
• LLM: 2 years (required)
• TensorFlow: 4 years (required)
• PyTorch: 4 years (required)
• Natural language processing: 4 years (required)
• Python: 3 years (required)

Work Location: Remote
Expected start date: 2025-04-0

• Design, implement, and optimize advanced NLP models using state-of-the-art architectures like Transformers, BERT, and GPT variants.
• Design and implement content-based image retrieval (CBIR) systems using embedding-based similarity search methods
• Develop and maintain end-to-end ML pipelines for text processing, image processing, model training, and evaluation using frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Develop and maintain image processing pipelines for feature extraction, embedding generation, and similarity comparison
• Implement and fine-tune large language models (LLMs) for various NLP tasks, including text classification, named entity recognition, sentiment analysis, and machine translation.
• Apply advanced NLP techniques such as word embeddings, contextual embeddings, and attention mechanisms to improve model performance.
• Develop solutions for semantic search, question-answering systems, and chatbots using LLMs and vector databases.
• Implement and optimize techniques for few-shot and zero-shot learning in NLP applications.
• Optimize image embedding models for efficiency and performance, considering factors like dimensionality reduction and computational resources
• Mentor junior team members and provide technical guidance
• Document processes, models, and experiments to ensure reproducibility and knowledge sharing
• Ensure all ML models and processes comply with data privacy and security standards
• Stay updated with the latest developments in machine learning, AI, and relevant technologies