Lead ML Engineer
Description For Lead ML Engineer
Salesforce, the leading Customer Company, is seeking a Lead ML Engineer to join their innovative team. This role combines cutting-edge AI technology with enterprise-scale challenges. You'll be at the forefront of developing generative AI services that impact thousands of customers across various industries. The position offers an opportunity to work with state-of-the-art LLMs and complex distributed systems.
As a Lead ML Engineer, you'll be responsible for designing and implementing scalable AI services, working closely with cross-functional teams including Product Managers, Architects, and Data Scientists. The role requires expertise in both traditional ML and modern generative AI techniques, with a focus on production-scale implementations.
The ideal candidate brings 8+ years of ML engineering experience, deep knowledge of LLMs, and strong programming skills in Java/Python. You'll work with modern tech stack including Kafka, Spark, and Docker, while applying your expertise in frameworks like TensorFlow or PyTorch.
Salesforce offers a unique opportunity to drive innovation in AI while working for a company that values both business success and positive social impact. You'll be part of a team that's shaping the future of business through AI+Data+CRM, working on challenges that haven't been solved before. The role combines technical excellence with leadership opportunities, making it perfect for someone who wants to make a significant impact in the AI industry while working with enterprise-scale systems.
Responsibilities For Lead ML Engineer
- Design and deliver scalable generative AI services for multi-tenant applications
- Drive system efficiencies through automation, capacity planning, and performance tuning
- Participate in periodic on-call rotations
- Partner with Product Managers, Architects, Data Scientists, and Researchers
- Design prototypes and bring innovative technologies to production
Requirements For Lead ML Engineer
- 8+ years of industry experience in ML engineering
- Experience with LLMs and prompt engineering
- Strong experience building and applying machine learning models
- Strong experience programming in Java/Python
- Experience with machine learning frameworks like TensorFlow or PyTorch
- Experience with distributed systems and frameworks (Kafka, Spark, Docker, Hadoop)
- Good working knowledge of Deep Learning and Machine Learning algorithms
- Strong leadership and collaboration skills
