We are looking for a Senior AI/ML Engineer to lead the development of cutting-edge AI/ML solutions, with a strong focus on LLMs, MLOps, and scalable cloud-based AI architectures. You will work on designing, building, and optimizing AI models for real-world applications, including LLM fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and multimodal AI. This role involves working with high-performance computing, distributed training, and large-scale data pipelines, making it ideal for candidates passionate about pushing AI boundaries.
Job Description
What you'll do:
- LLM Development & Optimization: Fine-tune, optimize, and deploy large language models (LLMs) .
- Scalable ML Systems: Architect and implement training and inference pipelines for large-scale AI models using PyTorch, or TensorFlow.
- Retrieval-Augmented Generation (RAG): Develop vector search-based retrieval systems to enhance LLM capabilities.
- End-to-End ML Workflow Ownership: Build and maintain robust MLOps pipelines using Kubeflow, MLflow.
- Cloud-Native AI Solutions: Design and deploy scalable AI/ML systems using AWS or Azure
- High-Performance Data Engineering: Develop and optimize large-scale data pipelines using Apache Spark, Dask, or Kafka for training and inference.
- Model Monitoring & Observability: Implement model performance tracking, drift detection, and self-healing mechanisms to maintain model robustness.
- Mentorship & Technical Leadership: Guide junior engineers, set best practices, and drive AI innovation across the organization.
What you'll bring:
- Experience: 5+ years of experience in AI/ML engineering, including LLM deployment, MLOps, and cloud-native machine learning.
- LLM & Deep Learning Expertise: Proficiency in Transformer architectures, PEFT (parameter-efficient fine-tuning), and tokenization strategies.
- Programming & Infrastructure: Strong coding skills in Python, Spark, and familiarity with C++.
- Data Engineering & Storage: Hands-on experience with Apache Iceberg and distributed computing frameworks.
- Cloud & Kubernetes: Proficiency in Kubernetes and CI/CD for AI pipelines.
- Soft Skills: Ability to collaborate cross-functionally, mentor engineers, and drive strategic AI initiatives.
About Us
SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 3,000 talented leaders, data scientists, and other professionals across over 30 countries.
Visit here, for more information about how we hire, what’s in it for you, our culture and values.
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