AI/ML Engineer Speech, RAG & Fine-Tuning
Ähdus Technology GmbH
Date: 9 hours ago
City: Rawalpindi
Contract type: Full time
Job Title: AI/ML Engineer Speech, RAG & Fine-Tuning
Location: Bahria Town, Phase 7, Rawalpindi
Employment Type: Full-time,Onsite (10AM - 7PM)
Job Description:
We are seeking a highly skilled AI/ML Engineer with expertise in speech-to-speech pipelines, open-source models, and LLM fine-tuning. The ideal candidate will work on designing, developing, and deploying cutting-edge speech and language AI solutions, integrating open-source frameworks with advanced fine-tuning methods to deliver production-ready systems.
Key Responsibilities:
Location: Bahria Town, Phase 7, Rawalpindi
Employment Type: Full-time,Onsite (10AM - 7PM)
Job Description:
We are seeking a highly skilled AI/ML Engineer with expertise in speech-to-speech pipelines, open-source models, and LLM fine-tuning. The ideal candidate will work on designing, developing, and deploying cutting-edge speech and language AI solutions, integrating open-source frameworks with advanced fine-tuning methods to deliver production-ready systems.
Key Responsibilities:
- Design and implement speech-to-speech pipelines using open-source models (Whisper, Wav2Vec, etc.).
- Develop and optimize speech-to-text (STT) and text-to-speech (TTS) systems leveraging Coqui or similar frameworks.
- Work with large language models (LLMs) such as LLaMA 2, LLaMA 3 for NLP applications.
- Apply LoRA and PEFT-based fine-tuning techniques to customize LLMs for domain-specific tasks.
- Build and optimize Retrieval-Augmented Generation (RAG)-based systems for knowledge-grounded responses.
- Develop and integrate agentic AI systems with reasoning and task automation capabilities.
- Collaborate with cross-functional teams (data engineers, product managers, software developers) to deliver scalable AI solutions.
- Monitor, evaluate, and optimize deployed AI models for accuracy, latency, and efficiency.
- Strong experience in AI/ML model development with open-source speech and language models.
- Hands-on experience with Whisper, Wav2Vec, Coqui TTS/STT frameworks.
- Proven track record with LLaMA 2, LLaMA 3 or similar LLMs.
- Proficiency in fine-tuning techniques: LoRA, PEFT, and parameter-efficient training.
- Experience in RAG-based systems for knowledge retrieval and contextual response generation.
- Familiarity with agentic AI frameworks for building task-oriented agents.
- Strong programming skills in Python, PyTorch, TensorFlow.
- Experience with Hugging Face, LangChain, and vector databases (FAISS, Pinecone, Weaviate, etc.).
- Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Strong problem-solving skills and ability to optimize model performance.
- Master’s or PhD in Computer Science, AI/ML, Data Science, or related field.
- Publications or projects in speech AI, LLM fine-tuning, or agentic AI.
- Experience with distributed training and model deployment at scale.
- Lunch provided by the company
- Medical Allowance
- Competitive compensation and growth opportunities.
- Opportunity to work with state-of-the-art open-source AI models.
- Collaborative environment with AI researchers and engineers.
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