Posted:1 week ago|
Platform:
On-site
Full Time
Highly skilled Senior Machine Learning Engineer with expertise in Deep Learning, Large Language Models (LLMs), and MLOps/LLMOps to design, optimize, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience in developing and scaling deep learning models, fine-tuning LLMs/ (e.g., GPT, Llama), and implementing robust deployment pipelines for production environments.
- Design, train, fine-tune and optimize deep learning models (CNNs, RNNs, Transformers) for NLP, computer vision, or multimodal applications.
- Fine-tune and adapt Large Language Models (LLMs) for domain-specific tasks (e.g., text generation, summarization, semantic similarity).
- Experiment with RLHF (Reinforcement Learning from Human Feedback) and other alignment techniques.
- Build and maintain end-to-end ML pipelines for training, evaluation, and deployment.
- Deploy LLMs and deep learning models in production environments using frameworks like FastAPI, vLLM, or TensorRT.
- Optimize models for low-latency, high-throughput inference (eg., quantization, distillation, etc.).
- Implement CI/CD workflows for ML systems using tools like MLflow, Kubeflow.
- Set up logging, monitoring, and alerting for model performance (drift, latency, accuracy).
- Work with DevOps teams to ensure scalability, security, and cost-efficiency of deployed models.
- 5-7 years of hands-on experience in Deep Learning, NLP, and LLMs.
- Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, and LLM frameworks.
- Experience with model deployment tools (Docker, Kubernetes, FastAPI).
- Knowledge of MLOps/LLMOps best practices (model versioning, A/B testing, canary deployments).
- Familiarity with cloud platforms (AWS, GCP, Azure).
Singularis Ventures
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