AI Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global professional services and accounting network offering comprehensive financial, tax, and advisory solutions. Known for embracing cutting-edge technology to drive business transformation, they foster an innovative and collaborative work culture. They empower their teams to leverage advanced technologies to solve complex challenges for clients worldwide.
About the role.
We are looking for an experienced AI Engineer to design and scale machine learning pipelines and large language model architectures in a hybrid work mode based in Bengaluru. You will work on cutting-edge Generative AI projects, optimizing model performance, fine-tuning LLMs, and driving robust LLMOps practices. This role demands 5 to 8 years of experience in building enterprise-grade AI solutions.
What you will do.
- Design ML pipelines for experiment management, model management, feature management, and model retraining.
- Design and develop APIs for model inferencing at scale.
- Utilize expertise in MLflow, SageMaker, Vertex AI, and Azure AI for streamlined deployments.
- Apply deep knowledge of GPU architectures to distributed training and serving of large language models.
- Execute model and data parallel training using frameworks like DeepSpeed and vLLM.
- Implement model fine-tuning and optimization techniques to achieve better latencies and accuracies while reducing resource requirements.
- Drive DevOps and LLMOps practices utilizing Kubernetes, Docker, and container orchestration.
- Build and maintain LLM orchestration frameworks such as Langchain, Langgraph, Langflow, and Flowise.
What you bring.
- 5–8 years of professional experience in software development and machine learning engineering.
- Mandatory expertise in Gen AI, LLMs, Hugging Face OSS LLMs, Python, and PyTorch/TensorFlow/Keras.
- Strong hands-on experience with Langchain, Langgraph, Docker, and Kubernetes.
- Proficiency in LLMOps tools including MLflow, LangFlow, Flowise, LlamaIndex, AWS Bedrock, SageMaker, Vertex AI, and Azure AI.
- Solid understanding of databases and data warehouses such as DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostgreSQL, Aurora, Spanner, and Google BigQuery.
- Familiarity with cloud platforms (AWS, Azure, GCP) and monitoring tools like FluentD, Kibana, Grafana, and Prometheus.
- Bachelor's or Master's degree in Engineering, Computer Applications, or a related field (B.Tech/MCA/BCA/M.Tech).
- Cloud certifications such as AWS Professional Solution Architect, AWS Machine Learning Specialty, or Azure Solutions Architect Expert are a strong bonus.
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