AI/ML Engineer

Responsibilities:

• Develop and fine-tune AI models using frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and LangChain.
• Build and optimize NLP and NLU pipelines leveraging libraries like NLTK and spaCy.
• Implement and integrate speech recognition/synthesis tools (e.g., Google Cloud Speech-to-Text, Amazon Polly) for voice interactions.
• Manage data storage and retrieval with vector databases (Faiss, Milvus) and graph databases (Neo4j, Amazon Neptune).
• Collaborate with cross-functional teams to integrate AI functionalities into engaging UX/UI experiences.
• Utilize model fine-tuning tools (e.g., Jupyter Notebooks, Google Colab) to iterate and improve performance.

Requirements:

• Proven experience in developing and fine-tuning AI/ML models with a focus on NLP and deep learning.
• Solid understanding of modern ML/DL architectures and data management in large-scale environments.
• Proficiency with Python and related AI frameworks, along with strong problem-solving skills.
• Excellent communication and collaboration skills in a fully remote work environment.

Tech Stack & Tools Requirements:

• AI Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, LangChain
• Fine-Tuning Tools: Jupyter Notebooks, Google Colab
• Databases: Faiss, Milvus, Neo4j, Amazon Neptune, MongoDB, PostgreSQL
• NLP & Speech: NLTK, spaCy, Google Cloud Speech-to-Text, Amazon Polly
• Development Tools: Coder, Copilot, GitHub, Visual Studio Code
• Open-Source & Integration: Llama 3.3, Modern BERT, Qwen, Nvidia’s Nemotron, Kong, KrakenD
• UX/UI & Simulation: React, Vue.js, Angular, Figma, Sketch, Adobe XD, Blender, Three.js
• CI/CD & Testing: Jenkins, GitHub Actions, Jest, Mocha, Chai; Monitoring with New Relic, Datadog
• Security (OWASP ZAP, SonarQube), User Authentication (Azure AD, OAuth 2.0), Streaming (WebRTC, Node.js).