What You Will Do

• Model Training & Evaluation: Full cycle of training, fine-tuning, and validating LLMs for virtual assistants, chatbots, and recommendation systems.
• Algorithm Development: Enhance efficiency and accuracy in natural language understanding and generation.
• LLMs in Cybersecurity: Apply models for threat analysis, detection, and automated security responses.
• Deployment Strategy: Partner with engineering teams to ensure scalable, reliable ML model deployment.
• Documentation & Standards: Define best practices and maintain clear records of models, pipelines, and metrics.
• Innovation: Explore emerging technologies, tools, and methods in language model development.
• Mentorship & Collaboration: Guide team members and work cross-functionally for cohesive project delivery.

Basic Qualifications

• Education & Experience: BA/BS or MS with 8+ years in machine learning, proven project portfolio.
• ML Systems & Algorithms: Strong background in ML engineering, deep learning, and statistical modeling; experience building scalable ML solutions.
• LLM Expertise: In-depth knowledge of Transformer-based architectures (e.g., GPT) and training/fine-tuning large-scale models; exposure to Agentic frameworks.
• NLP Skills: Data preprocessing (tokenization, stemming, lemmatization), handling ambiguity and context, and transfer learning for domain/language adaptation.
• Applications: Applied LLMs in chatbots, content generation, semantic search, and related use cases.
• Data & Evaluation: Skilled in data annotation strategies and model evaluation with appropriate metrics.
• Scalability & Deployment: Experience deploying LLMs to production with efficiency, reliability, and scalability.

Preferred Qualifications:

• Degree in Computer Science, Data Science, Statistics, Computational Linguistics or a related field.
• Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch)
• Excellent problem-solving and communication skills, with the ability to explain sophisticated concepts to non-technical partners
  • Proven experience to work collaboratively in multi-functional teams