Salesforce is looking for experienced Machine Learning Engineer (MLE) to be part of Agentforce Knowledge Foundation team building the next-gen Retrieval-Augmented Generation (RAG), leveraging advanced generative AI services, pipelines, and components to drive the development and delivery of Agentforce. You will work on and ship impactful generative AI platforms, applications, and products used by millions of people every day.

The team:

Agentforce Knowledge Foundations India team is a group of applied data scientists, machine learning engineers and software engineers that share a passion for designing data products, and building Generative AI services@scale and to help in bringing Generative AI services to production. We love to learn, teach and help each other, and we are looking for people with a collaborative attitude and openness to others' ideas.

The role:

You will play a critical role in incorporating artificial intelligence and generative AI into the Salesforce. You will participate in the end-to-end AI product development lifecycle. You will design and develop the scalable generative AI system and services in the domain of RAG, Enterprise Knowledge Graph, fine-tuned LLM deployments, and partner with AI Platform Engineers, Data Platform Engineers to define requirements, design and develop reusable workflow and ML pipeline.

What you’ll do:

• Design and deliver scalable generative AI services that can be integrated with many applications, thousands of tenants, and run at scale in production.

• Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring and root cause analysis.

• Participate in periodic on-call rotations and be available for critical issues.

• Partner with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production

Required Skills:

• 10+ years of software engineering experience; including 5+ years of industry experience of ML engineering in building AI systems and/or services.

• Experience with distributed, scalable systems and modern data stack, messaging and processing frameworks, including Spark / Flink, Hadoop, Kafka, Docker, etc.

• Strong experience programming in Java / Python, and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

• Experience with LLMs and prompt engineering.

• Familiarity with Vector databases (Milvus / Pinecone), and applied generative AI frameworks like LangChain, LlamaIndex, RAG pipelines.

• Proven ability to implement, operate, and deliver results via innovation at large scale

• Knowledge of public cloud Data & AI services, cloud-native architecture patterns (AWS/GCP).

• Good working knowledge of Deep Learning and Machine Learning algorithms. In the very least, you have a strong interest in this domain, as exemplified by coursework you've taken and personal projects you developed.

• Grit, drive and a strong feeling of ownership coupled with collaboration and leadership.

Preferred Skills:

• Experience in developing Generative AI systems at Scale with complex business use cases and large scale of unstructured data.

• Strong Machine Learning Engineering background and familiarity with state-of-the-art generative AI techniques especially for NLP.

• Expertise with applying LLMs, prompt design, and fine-tuning methods.

• Strong background in ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian methods.

• Fantastic problem solver; ability to solve problems that the world has not solved before.

• Excellent written and spoken communication skills.

• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams.