Lead AI/ML Engineer (LMTS) – LLM Post-Training & Fine-Tuning
Salesforce · India
| Company | Salesforce |
|---|---|
| Role | Lead AI/ML Engineer (LMTS) – LLM Post-Training & Fine-Tuning |
| Location | India |
| Work mode | Hybrid |
| Experience | 6+ years |
| Job type | Full-time |
About this job
Salesforce is hiring a Lead AI/ML Engineer (LMTS) in India to improve open-weight language models for business use through further training. This is a hands-on model training role, not prompt engineering or wrapping a hosted model.
You will own the full loop: generating and curating training data, running SFT and LoRA experiments, trying preference or reinforcement methods when justified, building strong evaluations, finding the root of model failures and serving models reliably. You will also mentor engineers. The role is hybrid.
Eligibility
- 10+ years of software engineering with technical leadership
- Strong Python for production systems
- Hands-on LLM post-training with SFT and LoRA/QLoRA
- Generating and curating training datasets
- Plus: DPO, RL, distillation or continued pre-training
Skills required
What you will do
- Train and adapt open-weight LLMs
- Run fine-tuning experiments to release
- Build the training data pipeline
- Design model quality evaluations
- Build reliable model serving
How to apply
- Open the official Salesforce job page with the Apply button and submit your application there.
- Tailor your resume to models you fine-tuned, datasets you built and measured quality gains.
Before the interview, prepare:
- SFT vs DPO: when to use each
- Avoiding test-set contamination
- Evaluating tool-use accuracy
- Diagnosing a regression after fine-tuning
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